2024

• Kangsan Lee, Jaehyuk Park, Sam Goree, David Crandall, Yong-Yeol Ahn, "Social signals predict contemporary art prices better than visual features, particularly in emerging markets," Scientific Reports, 2024. (impact factor 4.6) [ Paper] [ bibtek]
• Long-Jing Hsu, Weslie Khoo, Manasi Swaminathan, Kyrie Jig Amon, Rasika Muralidharan, Hiroki Sato, Min Min Thant, Anna Kim, Katherine M Tsui, David J Crandall, Selma Šabanovic, "Let's Talk About You: Development and Evaluation of an Autonomous Robot to Support Ikigai Reflection in Older Adults," IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2024. [ Paper] [ bibtek]
• Xizi Wang, Feng Cheng, Gedas Bertasius, "LoCoNet: Long-Short Context Network for Active Speaker Detection," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [ Paper] [ bibtek]
• Ziwei Zhao, Yuchen Wang, Chuhua Wang, "Fusing Personal and Environmental Cues for Identification and Segmentation of First-Person Camera Wearers in Third-Person," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [ Paper] [ bibtek]
• Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Triantafyllos Afouras, Kumar Ashutosh, Vijay Baiyya, Siddhant Bansal, Bikram Boote, Eugene Byrne, Zach Chavis, Joya Chen, Feng Cheng, Fu-Jen Chu, Sean Crane, Avijit Dasgupta, Jing Dong, Maria Escobar, Cristhian Forigua, Abrham Gebreselasie, Sanjay Haresh, Jing Huang, Md Mohaiminul Islam, Suyog Jain, Rawal Khirodkar, Devansh Kukreja, Kevin J Liang, Jia-Wei Liu, Sagnik Majumder, Yongsen Mao, Miguel Martin, Effrosyni Mavroudi, Tushar Nagarajan, Francesco Ragusa, Santhosh Kumar Ramakrishnan, Luigi Seminara, Arjun Somayazulu, Yale Song, Shan Su, Zihui Xue, Edward Zhang, Jinxu Zhang, Angela Castillo, Changan Chen, Xinzhu Fu, Ryosuke Furuta, Cristina Gonzalez, Prince Gupta, Jiabo Hu, Yifei Huang, Yiming Huang, Weslie Khoo, Anush Kumar, Robert Kuo, Sach Lakhavani, Miao Liu, Mi Luo, Zhengyi Luo, Brighid Meredith, Austin Miller, Oluwatumininu Oguntola, Xiaqing Pan, Penny Peng, Shraman Pramanick, Merey Ramazanova, Fiona Ryan, Wei Shan, Kiran Somasundaram, Chenan Song, Audrey Southerland, Masatoshi Tateno, Huiyu Wang, Yuchen Wang, Takuma Yagi, Mingfei Yan, Xitong Yang, Zecheng Yu, Shengxin Cindy Zha, Chen Zhao, Ziwei Zhao, Zhifan Zhu, Jeff Zhuo, Pablo Arbelaez, Gedas Bertasius, Dima Damen, Jakob Engel, Giovanni Maria Farinella, Antonino Furnari, Bernard Ghanem, Judy Hoffman, C.V. Jawahar, Richard Newcombe, Hyun Soo Park, James Rehg, Yoichi Sato, Manolis Savva, Jianbo Shi, Mike Zheng Shou, Michael Wray, "Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [ bibtek]
• Long-Jing Hsu, Philip Stafford, Weslie Khoo, Manasi Swaminathan, Kyrie Jig Amon, Hiroki Sato, Kate Tsui, David Crandall, Selma Sabanovic, "``Give it time:'' Longitudinal Panels Scaffold Older Adults' Learning and Robot Co-Design," ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024. [ Paper] [ bibtek]
• Satoshi Tsutsui, Yanwei Fu, David Crandall, "Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2024. (impact factor = 17.861) [ Paper] [ bibtek]
• Vibhas Vats, Sripad Joshi, David Crandall, Md. Alimoor Reza, Soon-heung Jung, "GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo," IEEE Winter Conference on Applications of Computer Vision (WACV), 2024. [ Paper] [ bibtek]
• Chuhua Wang, Md Alimoor Reza, Vibhas Vats, Yingnan Ju, Nikhil Thakurdesai, Yuchen Wang, David Crandall, Soon-heung Jung, Jeongil Seo, "Deep learning-based 3D reconstruction from multiple images: A survey," Neurocomputing, 2024. [ bibtek]
• Xiaomeng Ye, David Leake, Yu Wang, Ziwei Zhao, David Crandall, "Network Implementation of CBR: Case Study of a Neural Network K-NN," International Conference on Case-based Reasoning (ICCBR), 2024. [ Paper] [ bibtek]
• Zachary Wilkerson, David Leake, Vibhas Vats, David Crandall, "Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach," International Conference on Case-based Reasoning (ICCBR), 2024. [ Paper] [ bibtek]
• David Leake, Zachary Wilkerson, David Crandall, "Combining Case-Based Reasoning with Deep Learning: Context and Ongoing Case Feature Learning Research," AAAI Workshop on Neuro-Symbolic Learning and Reasoning in the Era of Large Language Models, 2024. [ bibtek]
• Long-Ling Hsu, Weslie Khoo, Peter Lenon Goshomi, Philip Stafford, Manasi Swaminathan, Kate Tsui, David Crandall, Selma Sabanovic, "Is Now a Good Time? Opportune Moments for Interacting with an Ikigai Support Robot," Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024. [ Paper] [ bibtek]
• Manasi Swaminathan, Long-Ling Hsu, Min Min Thant, Kyrie Jig Amon, Anna Kim, Kate Tsui, Selma Sabanovic, David Crandall, Weslie Khoo, "If [YourName] can code, so can you! End-user robot programming for non-experts," Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024. [ Paper] [ bibtek]

2023

• Long-Jing Hsu, Waki Kamino, Weslie Khoo, Katherine Tsui, David Crandall, Selma Sabanovic, "Working Together Toward ikigai: Co-Designing Robots That Can Help Us Achieve Meaning and Purpose in Life," XRDS: Crossroads, 2023. [ bibtek]
• Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, Gedas Bertasius, "VindLU: A recipe for Effective Video-and-Language Pretraining," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [ Paper] [ bibtek]
• Sam Goree, Weslie Khoo, David Crandall, "Correct for Whom? Subjectivity and the Evaluation of Personalized Image Aesthetics Assessment Models," AAAI Conference on Artificial Intelligence, 2023. (Oral, 19.6% acceptance rate) [ Paper] [ bibtek]
• Tianfei Zhou, Fatih Porikli, David Crandall, Luc Van Gool, Wenguan Wang, "A Survey on Deep Learning Techniques for Video Segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023. (impact factor 17.861, accepted, to appear) [ Paper] [ bibtek]
• Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Yuchen Wang, Ella Atkins, David Crandall, "DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023. (impact factor = 17.861) [ Paper] [ bibtek]
• Sam Goree, David Crandall, Norman Su, "``It Was Really All About Books:'' Speech-like Techno-Masculinity in the Rhetoric of Dot-Com Era Web Design Books," ACM Transactions on Computer-Human Interaction, 2023. (impact factor = 3.147) [ Paper] [ bibtek]
• Junbo Yin, Jianbing Shen, Xin Gao, David Crandall, Ruigang Yang, "Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023. (impact factor = 17.861) [ Paper] [ bibtek]
• Filippo Menczer, David Crandall, Yong-Yeol Ahn, Apu Kapadia, "Addressing the harms of AI-generated inauthentic content," Nature Machine Intelligence, 2023. (impact factor = 25.898) [ bibtek]
• Imran Kabir, Shaurya Shubham, Vijayalaxmi Bhimrao Maigur, Mahesh Ravindra Latnekar, Mayank Kumar Raunak, Nikhil Shripad Thakurdesai, David Crandall, Md Reza, "Few-shot segmentation and Semantic Segmentation for Underwater Imagery," IEEE International Conference on Intelligent Robots and Systems (IROS), 2023. [ bibtek]
• Zheng Chen, Zhengming Ding, David Crandall, Lantao Liu, "Polyline Generative Navigable Space Segmentation for Autonomous Visual Navigation," IEEE International Conference on Intelligent Robots and Systems (IROS), 2023. [ bibtek]
• Zachary Wilkerson, Vibhas Vats, Karan Acharya, David Leake, David Crandall, "Examining the Impact of Network Architecture on Extracted Feature Quality for CBR," International Conference on Case-based Reasoning (ICCBR), 2023. [ Paper] [ bibtek]
• Long-Jing Hsu, Weslie Khoo, Natasha Randall, Waki Kamino, Swapna Joshi, Hiroki Sato, David Crandall, Kate Tsui, Selma Sabanovic, "Finding Its Voice: Exploring the Influence of Robot Voices on Fit, Social Attributes, and Willingness Among Older Adults in the U.S. and Japan," IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023. [ Paper] [ bibtek]
• Jane Yang, Linda Smith, David Crandall, Chen Yu, "Using manual actions to create visual saliency: an outside-in solution to sustained attention and joint attention," Annual Conference of the Cognitive Science Society (CogSci), 2023. [ bibtek]
• Zheng Chen, Zhengming Ding, David Crandall, Lantao Liu, "Polyline Generative Navigable Space Segmentation for Autonomous Visual Navigation," IEEE Robotics and Automation Letters (RA-L), 2023. (impact factor 3.741) [ bibtek]
• Sam Goree, David Crandall, "Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision," IEEE CVPR Joint International Third Ego4D and Eleventh EPIC Workshop, 2023. [ Paper] [ bibtek]
• Weslie Khoo, Long-Jing Hsu, Kyrie Jig Amon, Pranav Vijay Chakilam, Wei-Chu Chen, Zachary Kaufman, Agness Lungu, Hiroki Sato, Erin Seliger, Manasi Swaminathan, Katherine Tsui, David Crandall, Selma Sabanovic, "Spill the Tea: When Robot Conversation Agents Support Well-being for Older Adults," Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2023. [ Paper] [ bibtek]
• David Leake, Zachary Wilkerson, Xiaomeng Ye, David Crandall, "Enhancing Case-Based Reasoning with Neural Networks," Compendium of Neurosymbolic Artificial Intelligence, 2023. [ bibtek]

2022

• Ziwei Zhao, David Leake, Xiaomeng Ye, David Crandall, "Generating Counterfactual Images: Toward a C2C-VAE Approach," International Conference on Case-based Reasoning Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems, 2022. [ Paper] [ bibtek]
• David Leake, "Case-Based Explanation: Making the Implicit Explicit," Proceedings of XCBR-22: Fourth Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems, ICCBR-22 Workshop Proceedings, 2022. In press [ Paper] [ bibtek]
• Chuhua Wang, Yuchen Wang, Mingze Xu, David Crandall, "Stepwise Goal-Driven Networks for Trajectory Prediction," IEEE Robotics and Automation Letters (RA-L), 2022. (impact factor = 3.741) [ Paper] [ bibtek]
• Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, Jiebo Luo, "Zero-Shot Video Object Segmentation with Co-Attention Siamese Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022. (impact factor = 17.861) [ bibtek]
• Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, Luc Van Gool, "Segmenting Objects from Relational Visual Data," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022. (impact factor = 17.861) [ bibtek]
• Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Christian Fuegen, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik, "Ego4D: Around the World in 3,000 Hours of Egocentric Video," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [ Paper] [ bibtek]
• Zhenhua Chen, Chuhua Wang, David Crandall, "Semantically Stealthy Adversarial Attacks against Segmentation Models," IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. (35.0% acceptance rate) [ Paper] [ bibtek]
• Zehua Zhang, David Crandall, "Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning," IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. (35.0% acceptance rate) [ Paper] [ bibtek]
• Satoshi Tsutsui, Xizi Wang, Guangyuan Weng, Yayun Zhang, David Crandall, Chen Yu, "Action Recognition based on Cross-Situational Action-object Statistics," IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2022. [ Paper] [ bibtek]
• Xiaomeng Ye, David Leake, David Crandall, "Case Adaptation with Neural Networks: Capabilities and Limitations," International Conference on Case-based Reasoning (ICCBR), 2022. [ Paper] [ bibtek]
• David Leake, Zachary Wilkerson, David Crandall, "Extracting Case Indices from Convolutional Neural Networks: A Comparative Study," International Conference on Case-based Reasoning (ICCBR), 2022. [ Paper] [ bibtek]
• Xiaomeng Ye, Ziwei Zhao, David Leake, David Crandall, "Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach," International Conference on Computational Creativity (ICCC), 2022. [ bibtek] [ Video]
• Zehua Zhang, David Crandall, Michael Proulx, Sachin Talathi, Abhishek Sharma, "Can Gaze Inform Egocentric Action Recognition?," ACM Symposium on Eye Tracking Research and Applications (ETRA), 2022. [ Paper] [ bibtek]
• Vibhas Vats, David Crandall, "Controlling the Quality of Distillation in Response-Based Network Compression," AAAI International Workshop on Practical Deep Learning in the Wild, 2022. [ Paper] [ bibtek]

2021

• Lawrence Gates, David Leake, "Evaluating CBR Explanation Capabilities: Survey and Next Steps," Proceedings of XCBR-21: Third Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems, ICCBR-21 Workshop Proceedings, 2021. [ Paper] [ bibtek]
• David Leake, Xiaomeng Ye, "Harmonizing Case Retrieval and Adaptation with Alternating Optimization," International Conference on Case-based Reasoning (ICCBR), 2021. [ Paper] [ bibtek]
• Joshua Smith, Md Alimoor Reza, Nathanael Smith, Jianxin Gu, Maha Ibrar, David Crandall, Sara Skrabalak, "Plasmonic Anti-counterfeit Tags with High Encoding Capacity Rapidly Authenticated with Deep Machine Learning," ACS Nano, 2021. (impact factor = 14.588) [ bibtek]
• Norman Su, David Crandall, "The Affective Growth of Computer Vision," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (Poster, 23.7% acceptance rate) [ Paper] [ bibtek] [ Video]
• Jagpreet Chawla, Nikhil Shripad Thakurdesai, Anuj Balasaheb Godase, Md Alimoor Reza, David Crandall, Soon-Heung Jung, "Error Diagnosis of Deep Monocular Depth Estimation Models," IEEE International Conference on Intelligent Robots and Systems (IROS), 2021. [ Paper] [ bibtek]
• Xiaomeng Ye, David Leake, Vahid Jalali, David Crandall, "Learning Adaptations for Case-Based Classification: A Neural Network Approach," International Conference on Case-based Reasoning (ICCBR), 2021. [ Paper] [ bibtek]
• Zachary Wilkerson, David Leake, David Crandall, "On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval," International Conference on Case-based Reasoning (ICCBR), 2021. [ Paper] [ bibtek]
• Yayun Zhang, Andrei Amatuni, Ellis Cain, Xizi Wang, David Crandall, Chen Yu, "Statistical learning of verb meaning," Annual Conference of the Cognitive Science Society (CogSci), 2021. [ Paper] [ bibtek]
• Ryan Peters, Andrei Amatuni, Sara Schroer, Shujon Naha, David Crandall, Chen Yu, "Are you with me? Modeling joint attention from egocentric vision," Annual Conference of the Cognitive Science Society (CogSci), 2021. [ Paper] [ bibtek]
• Andrei Amatuni, Sara Schroer, Ryan Peters, Md Alimoor Reza, Yayun Zhang, David Crandall, Chen Yu, "In-the-Moment Visual Information Determines Learning," Annual Conference of the Cognitive Science Society (CogSci), 2021. [ Paper] [ bibtek]
• Yuchen Wang, Mingze Xu, John Paden, Lara Koenig, Geoffrey Fox, David Crandall, "Deep Tiered Image Segmentation for Detecting Internal Ice Layers in Radar Imagery," IEEE International Conference on Multimedia and Expo (ICME), 2021. (Oral, 15% acceptance rate) [ Paper] [ bibtek]
• Sam Goree, Bardia Doosti, David Crandall, Norman Su, "Investigating the Homogenization of Web Design: A Mixed-Methods Approach," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2021. (Oral, 26% acceptance rate) [ Paper] [ bibtek]
• Satoshi Tsutsui, Yanwei Fu, David Crandall, "Whose hand is this? Person Identification from Egocentric Hand Gestures," IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [ Paper] [ bibtek] [ Video]
• Shujon Naha, Qingyang Xiao, Prianka Banik, Md Alimoor Reza, David Crandall, "Part Segmentation of Unseen Objects Using Keypoint Guidance," IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [ Paper] [ bibtek] [ Video]
• Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, David Crandall, "Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features," IJCAI Workshop on Deep Learning, Case-Based Reasoning, and AutoML: Present and Future Synergies, 2021. [ Paper] [ bibtek] [ Video]
• Chia-Fang Chung, Alejandra Ramos, Pei-Ni Chiang, Chien-Chun Wu, Connie Anne Tan, Weslie Khoo, David Crandall, "Computer Vision for Dietary Assessment," CHI Workshop on Realizing AI in Healthcare: Challenges Appearing in the Wild, 2021. [ Paper] [ bibtek] [ Video]
• David Leake, Xiaomeng Ye, David Crandall, "Supporting Case-Based Reasoning with Neural Networks: An Illustration for Case Adaptation," AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE), 2021. [ Paper] [ bibtek]

2020

• Bardia Doosti, Shujon Naha, Majid Mirbagheri, David Crandall, "HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Poster, 22.1% acceptance rate) [ Paper] [ bibtek] [ Video] [ Project page]
• Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, Steven Hoi, "Learning Video Object Segmentation from Unlabeled Videos," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Poster, 22.1% acceptance rate) [ Paper] [ bibtek]
• Zehua Zhang, Ashish Tawari, Sujitha Martin, David Crandall, "Interaction Graph for Object Importance Estimation in On-road Driving Videos," IEEE Conference on Robotics and Automation (ICRA), 2020. (Oral, 42% acceptance rate) [ Paper] [ bibtek] [ Video]
• Mang Ye, Jianbing Shen, David Crandall, Ling Shao, Jiebo Luo, "Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification," European Conference on Computer Vision (ECCV), 2020. (27% acceptance rate) [ Paper] [ bibtek]
• Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, Chen Yu, "A Computational Model of Early Word Learning from the Infant's Point of View," Annual Conference of the Cognitive Science Society (CogSci), 2020. (Oral, 22% acceptance rate) [ Paper] [ bibtek] [ Video]
• Rakibul Hasan, David Crandall, Mario Fritz, Apu Kapadia, "Automatically Detecting Bystanders in Photos to Reduce Privacy Risks," IEEE Security and Privacy (Oakland), 2020. [ Paper] [ bibtek] [ Video]
• Shujon Naha, Md Alimoor Reza, Chen Yu, David Crandall, "Localizing novel attended objects in egocentric views," British Machine Vision Conference (BMVC), 2020. (Poster, 29.1% acceptance rate) [ Paper] [ bibtek]
• Lei Yuan, Violet Xiang, David Crandall, Linda Smith, "Learning the generative principles of a symbol system from limited examples," Cognition, 2020. (impact factor = 3.537) [ Paper] [ bibtek]
• Roberto Hoyle, Luke Stark, Qatrunnada Ismail, David Crandall, Apu Kapadia, Denise Anthony, "Privacy Norms and Preferences for Photos Posted Online," ACM Transactions on Computer-Human Interaction, 2020. (impact factor = 2.227) [ Paper] [ bibtek]
• David Leake, David Crandall, "Bringing Case Based Reasoning to Deep Learning," International Conference on Case-Based Reasoning Special Track on Challenges and Promises, 2020. [ Paper] [ bibtek]
• Sam Goree, David Crandall, "Studying Empirical Color Harmony in Design," IEEE Conference on Computer Vision and Pattern Recognition Workshop on Computer Vision for Fashion, Art, and Design, 2020. [ Paper] [ bibtek]
• Xiaomeng Ye, David Leake, William Huibregtse, Mehmet Dalkilic, "Applying Class-to-Class Siamese Networks to Explain Classifications with Supportive and Contrastive Cases," International Conference on Case-based Reasoning (ICCBR), 2020. [ Paper] [ bibtek]
• Md Alimoor Reza, Kai Chen, Akshay Naik, David Crandall, Soon-Heung Jung, "Automatic dense annotation for monocular 3d scene understanding," IEEE Access, 2020. (impact factor = 4.098) [ Paper] [ bibtek]
• Md Alimoor Reza, Zhenhua Chen, David Crandall, "Deep Neural Network-based Detection and Verification of Microelectronic Images," Journal of Hardware and Systems Security, 2020. [ Paper] [ bibtek]
• Sam Goree, Bardia Doosti, David Crandall, Norman Su, "Yes, websites really are starting to look more similar," The Conversation, 2020. [ Paper] [ bibtek]
• Ishtiak Zaman, David Crandall, "Genetic-GAN: Synthesizing images between two domains by genetic crossover," European Conference on Computer Vision Workshop on Advances in Manipulation, 2020. [ bibtek]
• Shujon Naha, Qingyang Xiao, Prianka Banik, Md Alimoor Reza, David Crandall, "Pose-guided knowledge transfer for object part segmentation," IEEE Conference on Computer Vision and Pattern Recognition Workshop on Visual Learning with Limited Labels, 2020. [ Paper] [ bibtek]
• Oluwanisola Ibikunle, John Paden, Maryam Rahnemoonfar, David Crandall, Masoud Yari, "Snow Radar Layer Tracking using an Iterative Neural Network Approach," IEEE International Geoscience and Remote Sensing Symposium, 2020. [ bibtek]

2019

• Victor Berger, Mingze Xu, Mohanad Al-Ibadi, Shane Chu, David Crandall, John Paden, Geoffrey Fox, "Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2019. (impact factor = 3.392) [ Paper] [ bibtek]
• Noam Levin, Saleem Ali, David Crandall, Salit Kark, "World Heritage in danger: Big data and remote sensing can help protect sites in conflict zones," Global Environmental Change, 2019. (impact factor = 6.371) [ bibtek]
• Satoshi Tsutsui, Yanwei Fu, David Crandall, "Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition," Advances in Neural Information Processing Systems (NeurIPS), 2019. (Poster, 21.6% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Zehua Zhang, Chen Yu, David Crandall, "A Self Validation Network for Object-Level Human Attention Estimation," Advances in Neural Information Processing Systems (NeurIPS), 2019. (Poster, 21.6% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Jianwei Yang, Zhile Ren, Mingze Xu, Xinlei Chen, David Crandall, Devi Parikh, Dhruv Batria, "Embodied Visual Recognition: Learning to Move for Amodal Perception," IEEE International Conference on Computer Vision (ICCV), 2019. (Poster, 25.0% acceptance rate) [ Paper] [ bibtek]
• Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry Davis, David Crandall, "Temporal Recurrent Networks for Online Action Detection," IEEE International Conference on Computer Vision (ICCV), 2019. (Poster, 25.0% acceptance rate) [ Paper] [ bibtek]
• Yu Yao, Mingze Xu, Chiho Choi, David Crandall, Ella Atkins, Behzad Dariush, "Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems," IEEE Conference on Robotics and Automation (ICRA), 2019. (Oral, 44% acceptance rate) [ Paper] [ bibtek]
• Rakibul Hasan, Yifang Li, Eman Hassan, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia, "Can Privacy Be Satisfying? On Improving Viewer Satisfaction for Privacy-Enhanced Photos Using Aesthetic Transforms," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2019. (Oral, 23.8% acceptance rate) [ Paper] [ bibtek]
• Wenguan Wang, Xiankai Lu, Jianbing Shen, David Crandall, Ling Shao, "Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks," IEEE International Conference on Computer Vision (ICCV), 2019. (Oral, 25.0% acceptance rate) [ Paper] [ bibtek]
• Yu Yao, Mingze Xu, Yuchen Wang, David Crandall, Ella Atkins, "Unsupervised Traffic Accident Detection in First-Person Videos," IEEE International Conference on Intelligent Robots and Systems (IROS), 2019. (Oral, 45.0% acceptance rate) [ Paper] [ bibtek]
• Md Alimoor Reza, Akshay Naik, Kai Chen, David Crandall, "Automatic Annotation for Semantic Segmentation in Indoor Scenes," IEEE International Conference on Intelligent Robots and Systems (IROS), 2019. (Oral, 45.0% acceptance rate) [ Paper] [ bibtek]
• Jangwon Lee, Bardia Doosti, Yupeng Gu, David Cartledge, David Crandall, Christopher Raphael, "Observing Pianist Accuracy and Form with Computer Vision," IEEE Winter Conference on Applications of Computer Vision (WACV), 2019. (Poster+Oral, 39% acceptance rate) [ Paper] [ bibtek]
• Suzanne Menzel, Katie Siek, David Crandall, "Hello Research! Developing an Intensive Research Experience for Undergraduate Women," ACM Technical Symposium on Computer Science Education (SIGCSE), 2019. (Oral, 34% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Jeremy Borjon, Sara Schroer, Sven Bambach, Lauren Slone, Drew Abney, David Crandall, Linda Smith, "A View of Their Own: Capturing the Egocentric View of Infants and Toddlers with Head-Mounted Cameras," Journal of Visualized Experiments, 2019. (impact factor = 1.325) [ bibtek]
• Hadar Karmazyn Raz, Drew Abney, David Crandall, Chen Yu, Linda Smith, "How do infants start learning object names in a sea of clutter?," Annual Conference of the Cognitive Science Society (CogSci), 2019. [ Paper] [ bibtek]
• Aniruddha Godbole, David Crandall, "Empowering Borrowers in their Choice of Lenders: Decoding Service Quality from Customer Complaints," ACM International Web Science Conference (WebSci), 2019. (Oral, 34.2% acceptance rate) [ Paper] [ bibtek]
• Katie Spoon, David Crandall, Katie Siek, "Towards Detecting Dyslexia in Children's Handwriting Using Neural Networks," ICML Workshop on AI for Social Good, 2019. Best poster award. [ Paper] [ bibtek] [ Project page]
• Satoshi Tsutsui, Dian Zhi, Md Alimoor Reza, David Crandall, Chen Yu, "Active Object Manipulation Facilitates Visual Object Learning: An Egocentric Vision Study," IEEE CVPR Workshop on Egocentric Perception, Interaction, and Computing (EPIC), 2019. [ Paper] [ bibtek]
• Zhenhua Chen, Chuhua Wang, Tiancong Zhao, David Crandall, "Generalized Capsule Networks with Trainable Routing Procedure," International Conference on Machine Learning Workshop on Generalization, 2019. [ Paper] [ bibtek]
• Tousif Ahmed, Rakibul Hasan, Kay Connelly, David Crandall, Apu Kapadia, "Conveying Situational Information to People with Visual Impairments," CHI Workshop on Addressing the Challenges of Situationally-Induced Impairments and Disabilities in Mobile Interaction, 2019. [ Paper] [ bibtek]
• David Crandall, "Artificial Intelligence and Manufacturing," Smart Factories: Issues of Information Governance, 2019. [ Paper] [ bibtek]
• Geoffrey Fox, Judy Qiu, David Crandall, Gregor Von Laszewski, Oliver Beckstein, John Paden, Ioannis Paraskevakos, Shantenu Jha, Fusheng Wang, Madhav Marathe, Anil Vullikanti, Thomas Cheatham, "Contributions to High-Performance Big Data Computing," Future Trends of HPC in a Disruptive Scenario, 2019. [ Paper] [ bibtek]

2018

• Sven Bambach, David Crandall, Linda Smith, Chen Yu, "Toddler-Inspired Visual Object Learning," Advances in Neural Information Processing Systems (NeurIPS), 2018. (Poster, 20.8% acceptance rate) [ Paper] [ bibtek]
• Mingze Xu, Chenyou Fan, Yuchen Wang, Michael Ryoo, David Crandall, "Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos," European Conference on Computer Vision (ECCV), 2018. (Poster) [ Paper] [ bibtek] [ Project page]
• Rakibul Hasan, Eman Hassan, Yifang Li, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia, "Viewer Experience of Obscuring Scene Elements in Photos to Enhance Privacy," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2018. (Oral, 25.7% acceptance rate) [ Paper] [ bibtek]
• Ashwin Vijayakumar, Michael Cogswell, Ramprasaath Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra, "Diverse Beam Search for Improved Description of Complex Scenes," AAAI Conference on Artificial Intelligence, 2018. (Poster, 24.6% acceptance rate) [ Paper] [ bibtek]
• Bo-chiuan Chen, Dong-Chul Seo, Hsien-Chang Lin, David Crandall, "A Framework for Estimating Sleep Timing from Digital Footprints," BMJ Innovations, 2018. (impact factor = 2.899) [ bibtek]
• Chenyou Fan, Zehua Zhang, David Crandall, "Deepdiary: Lifelogging image captioning and summarization," Journal of Visual Communication and Image Representation, 2018. (impact factor = 2.164) [ bibtek] [ Project page]
• Noam Levin, Saleem Ali, David Crandall, "Utilizing remote sensing and big data to quantify conflict intensity: The Arab Spring as a case study," Applied Geography, 2018. (impact factor = 2.56) [ Paper] [ bibtek]
• Satoshi Tsutsui, Sven Bambach, David Crandall, Chen Yu, "Estimating Head Motion from Egocentric Vision," ACM International Conference on Multimodal Interaction (ICMI), 2018. [ Paper] [ bibtek]
• Zehua Zhang, Sven Bambach, David Crandall, Chen Yu, "From Coarse Attention to Fine-Grained Gaze: A Two-stage 3D Fully Convolutional Network for Predicting Eye Gaze in First Person Video," British Machine Vision Conference (BMVC), 2018. (Oral, 4.3% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Mingze Xu, Aidean Sharghi, Xin Chen, David Crandall, " Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition," IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. (40% acceptance rate) [ Paper] [ bibtek]
• Mingze Xu, Chenyou Fan, John Paden, Geoffrey Fox, David Crandall, "Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction," IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. (40% acceptance rate) [ Paper] [ bibtek]
• Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Victor Berger, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, Wesley Van Wychen, "Crossover Analysis and Automated Layer-Tracking Assessment of the Extracted DEM of the Basal Topography of the Canadian Arctic Archipelago Ice-Cap," IEEE Radar Conference, 2018. [ Paper] [ bibtek]
• Victor Berger, Mingze Xu, David Crandall, John Paden, Geoffrey Fox, "Automated Tracking of 2d and 3d Ice Radar Imagery using Viterbi and TRW-S," IEEE International Geoscience and Remote Sensing Symposium, 2018. [ bibtek]
• Satoshi Tsutsui, Tommi Kerola, Shunta Saito, David Crandall, "Minimizing Supervision for Free-space Segmentation," IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Autonomous Driving (WAD), 2018. [ Paper] [ bibtek]
• Jangwon Lee, Haodan Tan, David Crandall, Selma Sabanovic, "Forecasting Hand Gestures for Human-Drone Interaction," ACM/IEEE International Conference on Human Robot Interaction (HRI), 2018. (Late-breaking Report) [ Paper] [ bibtek]

2017

• Tousif Ahmed, Roberto Hoyle, Patrick Shaffer, Kay Connelly, David Crandall, Apu Kapadia, "Understanding the Physical Safety, Security, and Privacy Concerns of People with Visual Impairments," IEEE Internet Computing, 2017. (impact factor = 2.0) [ bibtek]
• Scott Workman, Menghua Zhai, David Crandall, Nathan Jacobs, "A unified model for near and remote sensing," IEEE International Conference on Computer Vision (ICCV), 2017. (Poster, 28% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Chenyou Fan, Jangwon Lee, Mingze Xu, Krishna Kumar Singh, Yong Jae Lee, David Crandall, Michael Ryoo, "Identifying first-person camera wearers in third-person videos," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (Poster, 29.0% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Wen Chen, David Crandall, Norman Su, "Understanding the Aesthetic Evolution of Websites: Towards a Notion of Design Periods," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2017. (Oral, 25.0% acceptance rate) [ Paper] [ bibtek]
• Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Borner, "An efficient system to fund science: from proposal review to peer-to-peer distributions," Scientometrics, 2017. (impact factor = 2.084) [ bibtek]
• Satoshi Tsutsui, David Crandall, "A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks," IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017. [ Paper] [ bibtek] [ Project page]
• Bardia Doosti, David Crandall, Norman Makoto Su, "A deep study into the history of web design," ACM International Web Science Conference (WebSci), 2017. (Oral, 35.3% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Sven Bambach, David Crandall, Linda Smith, Chen Yu, "An Egocentric Perspective on Active Vision and Visual Object Learning in Toddlers," IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2017. (Oral, 37.1% acceptance rate) [ Paper] [ bibtek]
• Mingze Xu, David Crandall, Geoffrey Fox, John Paden, "Automatic estimation of ice bottom surfaces from radar imagery," IEEE International Conference on Image Processing (ICIP), 2017. (Oral, 45.0% acceptance rate) [ Paper] [ bibtek]
• Eman Hassan, Rakibul Hasan, Patrick Shaffer, David Crandall, Apu Kapadia, "Cartooning for enhanced privacy in lifelogging and streaming video," IEEE Conference on Computer Vision and Pattern Recognition Workshop on Computer Vision Challenges and Opportunities for Privacy and Security (CVPR CV-COPS), 2017. [ Paper] [ bibtek]
• Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David Crandall, Robert Templeman, "Addressing supply chain risks of microelectronic devices through computer vision," IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2017. [ Paper] [ bibtek]
• Sven Bambach, Zehua Zhang, David Crandall, Chen Yu, "Exploring inter-observer differences in first-person object views using deep learning models," IEEE International Conference on Computer Vision Workshop on Mutual Benefits of Cognitive and Computer Vision, 2017. [ Paper] [ bibtek]
• Jangwon Lee, Jingya Wang, David Crandall, Selma Sabanovic, Geoffrey Fox, "Real-Time, Cloud-based Object Detection for Unmanned Aerial Vehicles," IEEE Robotic Computing, 2017. (Oral) [ Paper] [ bibtek]
• Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, Wesley Van Wychen, "DEM Extraction of the Basal Topography of the Canadian Archipelago Ice Caps via 2d automated layer-tracking," IEEE International Geoscience and Remote Sensing Symposium, 2017. (Oral) [ Paper] [ bibtek]
• Satoshi Tsutsui, Guilin Meng, Xiaohui Yao, David Crandall, Ying Ding, "Analyzing figures of brain images from Alzheimer's Disease Papers," iConference, 2017. [ Paper] [ bibtek]

2016

• Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David Crandall, Dhruv Batra, "Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles," Advances in Neural Information Processing Systems (NeurIPS), 2016. (Poster, 22.7% acceptance rate) [ Paper] [ bibtek]
• Mohammed Korayem, Robert Templeman, Dennis Chen, David Crandall, Apu Kapadia, "Enhancing Lifelogging Privacy by Detecting Screens," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2016. Honorable Mention Award. (CHI Note, 23.4% acceptance rate) Honorable Mention Award! [ Paper] [ bibtek] [ Project page]
• David Crandall, Yunpeng Li, Stefan Lee, Daniel Huttenlocher, "Recognizing landmarks in large-scale social image collections," Visual Analysis and Geolocalization of Large Scale Imagery, 2016. [ Paper] [ bibtek]
• Mohammed Korayem, Khalifeh Aljadda, David Crandall, "Sentiment/Subjectivity Analysis Survey for Languages other than English," Social Network Analysis and Mining, 2016. [ bibtek]
• Noam Levin, David Crandall, Salit Kark, "Scale matters: differences between local, regional, and global analyses (letter to the editor)," Ecological Applications, 2016. (impact factor = 4.126) [ bibtek]
• Tousif Ahmed, Patrick Shaffer, Kay Connelly, David Crandall, Apu Kapadia, "Addressing Physical Safety, Security, and Privacy for People with Visual Impairments," USENIX Symposium on Usable Privacy and Security (SOUPS), 2016. (Oral, 27.8% acceptance rate) [ Paper] [ bibtek]
• Sven Bambach, David Crandall, Linda Smith, Chen Yu, "Active Viewing in Toddlers Facilitates Visual Object Learning: An Egocentric Vision Approach," Annual Conference of the Cognitive Science Society (CogSci), 2016. (Oral, 34% acceptance rate) [ Paper] [ bibtek]
• Jingya Wang, Mohammed Korayem, Saul Blanco, David Crandall, "Tracking Natural Events through Social Media and Computer Vision," ACM International Conference on Multimedia (MM), 2016. [ Paper] [ bibtek] [ Project page]
• Sven Bambach, Linda Smith, David Crandall, Chen Yu, "Objects in the Center: How the Infant's Body Constrains Infant Scenes," IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2016. Best paper award. (Oral, 33.7% acceptance rate) Best paper award! [ Paper] [ bibtek]
• Chenyou Fan, David Crandall, "DeepDiary: Automatically Captioning Lifelogging Image Streams," European Conference on Computer Vision International Workshop on Egocentric Perception, Interaction, and Computing (EPIC), 2016. [ Paper] [ bibtek] [ Project page]
• Tousif Ahmed, Roberto Hoyle, Patrick Shaffer, Kay Connelly, David Crandall, Apu Kapadia, "Considering Privacy Implications of Assistive Devices for People with Visual Impairments," CHI Workshop on Interactive Systems in Healthcare (WISH), 2016. [ bibtek]
• Kathy Tang, David Crandall, "Applying Deep Learning to Improve Maritime Situational Awareness," ACM International Conference on Knowledge Discovery and Data Mining Workshop on Large-scale Deep Learning for Data Mining, 2016. [ bibtek]
• Sven Bambach, "Analyzing Hands with First-Person Computer Vision," Indiana University, 2016. (Ph.D. Dissertation) [ Paper] [ bibtek]
• Stefan Lee, "Data-driven Computer Vision for Science and the Humanities," Indiana University, 2016. (Ph.D. Dissertation) [ bibtek]
• Sumit Gupta, "Evaluation of Convolutional Neural Networks for Infrared, Fine-grained Recognition, and Ego-centric Scene Classification," Indiana University, 2016. (M.S. Thesis) [ bibtek]
• Manu Singh, "Tag selection and propagation for large-scale visual landmark recognition," Indiana University, 2016. (M.S. Thesis) [ bibtek]

2015

• Noam Levin, Salit Kark, David Crandall, "Where have all the people gone? Enhancing global conservation using night lights and social media," Ecological Applications, 2015. (impact factor = 4.126) [ Paper] [ bibtek]
• Kun Duan, Dhruv Batra, David Crandall, "Human pose estimation through composite multi-layer models," Signal Processing, 2015. (impact factor = 2.238) [ Paper] [ bibtek] [ Project page]
• Sven Bambach, Stefan Lee, David Crandall, Chen Yu, "Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions," IEEE International Conference on Computer Vision (ICCV), 2015. (Poster, 30.3% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Sven Bambach, David Crandall, Chen Yu, "Viewpoint Integration for Hand-Based Recognition of Social Interactions from a First-Person View," ACM International Conference on Multimodal Interaction (ICMI), 2015. (Poster, 41% acceptance rate) [ Paper] [ bibtek]
• Stefan Lee, Nicolas Maisonneuve, David Crandall, Alexei Efros, Josef Sivic, "Linking past to present: Discovering style in two centuries of architecture," IEEE International Conference on Computational Photography (ICCP), 2015. (Oral, 24% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Tousif Ahmed, Roberto Hoyle, Kay Connelly, David Crandall, Apu Kapadia, "Privacy Concerns and Behaviors of People with Visual Impairments," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2015. (Full paper, 23% acceptance rate) [ Paper] [ bibtek]
• Stefan Lee, Haipeng Zhang, David Crandall, "Predicting Geo-informative Attributes in Large-scale Image Collections using Convolutional Neural Networks," IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. (Oral and poster, 36.7% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Roberto Hoyle, Robert Templeman, Denise Anthony, David Crandall, Apu Kapadia, "Sensitive Lifelogs: A Privacy Analysis of Photos from Wearable Cameras," ACM CHI Conference on Human Factors in Computing Systems (CHI), 2015. (CHI Note) [ Paper] [ bibtek]
• Supun Kamburugamuve, Hengjing He, Geoffrey Fox, David Crandall, "Cloud-based parallel implementation of SLAM for mobile robots," International Supercomputing Conference (ISC) Cloud & Big Data Conference, 2015. [ bibtek]
• Roberto Hoyle, Apu Kapadia, David Crandall, "Challenges in Running Wearable Camera-Related User Studies," ACM Conference on Computer-Supported Cooperative Work and Social Computing Workshop on The Future of Networked Privacy: Challenges and Opportunities, 2015. [ bibtek]
• Mohammed Korayem, "Social and Egocentric Image Classification for Scientific and Privacy Applications," Indiana University, 2015. (Ph.D. Dissertation) [ Paper] [ bibtek]
• Devendra Dhami, "Morphological Classification of Galaxies into Spirals and Non-Sprirals," Indiana University, 2015. (M.S. Thesis) [ bibtek]
• Harsh Seth, "Automated Answering Apps for People with Visual Impairments using Google Glass," Indiana University, 2015. (M.S. Thesis) [ bibtek]

2014

• Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Borner, "Response: ``Why we still need grant peer review''," EMBO Reports, 2014. (impact factor = 7.189) [ bibtek]
• Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Borner, "From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review," EMBO Reports, 2014. (impact factor = 7.189) [ Paper] [ bibtek]
• Kun Duan, David Crandall, Dhruv Batra, "Multimodal Learning in Loosely-organized Web Images," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (Poster, 29.9% acceptance rate) [ Paper] [ bibtek]
• Robert Templeman, Mohammed Korayem, David Crandall, Apu Kapadia, "PlaceAvoider: Steering First-Person Cameras away from Sensitive Spaces," Network and Distributed System Security Symposium (NDSS), 2014. (Oral, 18.6% acceptance rate) [ Paper] [ bibtek]
• Stefan Lee, Jerome Mitchell, David Crandall, Geoffrey Fox, "Estimating Bedrock and Surface Layer Boundaries and Confidence Intervals in Ice Sheet Radar Imagery using MCMC," IEEE International Conference on Image Processing (ICIP), 2014. (Oral, 44% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, Apu Kapadia, "Privacy Behaviors of Lifeloggers using Wearable Cameras," ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2014. (Oral, 20.7% acceptance rate) [ Paper] [ bibtek]
• Sven Bambach, John Franchak, David Crandall, Chen Yu, "Detecting Hands in Children's Egocentric Views to Understand Embodied Attention during Social Interaction," Annual Conference of the Cognitive Science Society (CogSci), 2014. (Oral, 41.0% acceptance rate) [ Paper] [ bibtek]
• Kun Duan, Luca Marchesotti, David Crandall, "Vehicle Recognition with Constrained Multiple Instance SVMs," IEEE Winter Conference on Applications of Computer Vision (WACV), 2014. (Oral and poster, 40% acceptance rate) [ Paper] [ bibtek]
• Haipeng Zhang, Zhixian Yan, Jun Yang, Emmanuel Munguia Tapia, David Crandall, "mFingerprint: Privacy-preserving user modeling with multimodal mobile device footprints," International Conference on Social Computing, Behavior-Cultural Modeling, & Prediction (SBP), 2014. (Oral, 24% acceptance rate) [ Paper] [ bibtek]
• Stefan Lee, Sven Bambach, David Crandall, John Franchak, Chen Yu, "This Hand is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video," IEEE Conference on Computer Vision and Pattern Recognition Workshop on Egocentric Vision, 2014. Best paper award winner. (Oral) Best paper award! [ Paper] [ bibtek]
• Robert Templeman, Roberto Hoyle, David Crandall, Apu Kapadia, "Reactive Security: Responding to Visual Stimuli from Wearable Cameras," Ubicomp Workshop on Usable Privacy and Security for Wearable and Domestic Ubiquitous Devices (UPSIDE), 2014. [ Paper] [ bibtek]
• Haipeng Zhang, "Analyzing the dynamics between the user-sensed data and the real world," Indiana University, 2014. (Ph.D. Dissertation) [ Paper] [ bibtek]
• Kun Duan, "Conditional random field models for structured visual object recognition," Indiana University, 2014. (Ph.D. Dissertation) [ bibtek]

2013

• David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher, "SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2013. (impact factor = 4.795) [ Paper] [ bibtek] [ Project page]
• Robert Templeman, Zahidur Rahman, David Crandall, Apu Kapadia, "PlaceRaider: Virtual Theft in Physical Spaces with Smartphones," Network and Distributed System Security Symposium (NDSS), 2013. (Oral, 18% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Sven Bambach, David Crandall, Chen Yu, "Understanding Embodied Visual Attention in Child-Parent Interaction," IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2013. (Oral, 33% acceptance rate) [ Paper] [ bibtek]
• Mohammed Korayem, David Crandall, "De-anonymizing users across heterogeneous social computing platforms," AAAI International Conference on Weblogs and Social Media (ICWSM), 2013. (Poster) [ Paper] [ bibtek]
• Haipeng Zhang, Nish Parikh, Gyanit Singh, Neel Sundaresan, "Chelsea Won, and You Bought a T-shirt: Characterizing the Interplay Between Twitter and E-Commerce," ASONAM, 2013. Best paper award! [ Paper] [ bibtek]
• Jerome Mitchell, David Crandall, Geoffrey Fox, Maryam Rahnemoonfar, John Paden, "A Semi-Automatic Approach for Estimating Bedrock and Surface Layers from Multichannel Coherent Radar Depth Sounder Imagery," SPIE Conference on Remote Sensing, 2013. (Oral) [ bibtek]
• Jingya Wang, Mohammed Korayem, David Crandall, "Observing the natural world with Flickr," International Conference on Computer Vision Workshop on Computer Vision for Converging Perspectives, 2013. Best paper award winner. (Oral) Best paper award! [ Paper] [ bibtek]
• Jerome Mitchell, David Crandall, Geoffrey Fox, John Paden, "Automatic Near Surface Estimation from Snow Radar Imagery," IEEE International Geoscience and Remote Sensing Symposium, 2013. (Oral) [ Paper] [ bibtek]

2012

• David Crandall, Noah Snavely, "Modeling people and places with internet photo collections," Communications of the ACM (CACM), 2012. (impact factor = 2.51) Also appeared in ACM Queue magazine [ Paper] [ bibtek]
• Kun Duan, Devi Parikh, David Crandall, Kristen Grauman, "Discovering Localized Attributes for Fine-grained Recognition," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. (Poster, 26% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Haipeng Zhang, Mohammed Korayem, David Crandall, Gretchen LeBuhn, "Mining Photo-sharing Websites to Study Ecological Phenomena," International World Wide Web Conference (WWW), 2012. (Oral, 12% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Kun Duan, Dhruv Batra, David Crandall, "A Multi-layer Composite Model for Human Pose Estimation," British Machine Vision Conference (BMVC), 2012. (Poster, 32% acceptance rate) [ Paper] [ bibtek]
• David Crandall, Geoffrey Fox, John Paden, "Layer-finding in radar echograms using probabilistic graphical models," IAPR International Conference on Pattern Recognition (ICPR), 2012. (Oral, 15% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Haipeng Zhang, Mohammed Korayem, Erkang You, David Crandall, "Beyond Co-occurrence: Discovering and Visualizing Tag Relationships from Geo-spatial and Temporal Similarities," ACM International Conference on Web Search and Data Mining (WSDM), 2012. (Oral, 8.3% acceptance rate) [ Paper] [ bibtek] [ Project page]
• Mohammed Korayem, Abdallah Mohamed, David Crandall, Roman Yampolskiy, "Learning visual features for the Avatar Captcha Recognition Challenge," International Conference on Machine Learning Applications (ICMLA), 2012. [ Paper] [ bibtek]
• Mohammed Korayem, Abdallah Mohamed, David Crandall, Roman Yampolskiy, "Solving Avatar Captchas automatically," International Conference on Advanced Machine Learning Technologies and Applications, 2012. (Oral) [ Paper] [ bibtek]
• Mohammed Korayem, David Crandall, Muhammad Abdul-Mageed, "Subjectivity and Sentiment Analysis of Arabic: A Survey," International Conference on Advanced Machine Learning Technologies and Applications, 2012. (Poster) [ Paper] [ bibtek]

2011

• David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher, "Discrete-Continuous Optimization for Large-scale Structure from Motion," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. Best paper runner-up. (Oral, 3.5% acceptance rate) Best paper runner-up! [ Paper] [ bibtek] [ Project page]
• David Crandall, Noah Snavely, "Networks of Landmarks, Photos, and People," Leonardo, 2011. [ Paper] [ bibtek]

2010

• David Crandall, Lars Backstrom, Daniel Cosley, Siddharth Suri, Daniel Huttenlocher, Jon Kleinberg, "Inferring Social Ties from Geographic Coincidences," Proceedings of the National Academy of Sciences (PNAS), 2010. (impact factor = 9.737) [ Paper] [ bibtek]

2009

• Yunpeng Li, David Crandall, Daniel Huttenlocher, "Landmark Classification in Large-scale Image Collections," IEEE International Conference on Computer Vision (ICCV), 2009. (Poster, 23.2% acceptance rate) [ Paper] [ bibtek]
• David Crandall, Lars Backstrom, Daniel Huttenlocher, Jon Kleinberg, "Mapping the World's Photos," International World Wide Web Conference (WWW), 2009. Best paper honorable mention. (Oral, 13% acceptance rate) Best paper honorable mention! [ Paper] [ bibtek] [ Project page]

2008

• David Crandall, Daniel Cosley, Daniel Huttenlocher, Jon Kleinberg, Sid Suri, "Feedback Effects between Similarity and Social Influence in Online Communities," ACM International Conference on Knowledge Discovery and Data Mining (KDD), 2008. (Oral, 18.6% acceptance rate) [ Paper] [ bibtek]
• David Crandall, "Part-based Statistical Models for Visual Object Class Recognition," Cornell University, 2008. (Ph.D. Dissertation) [ Paper] [ bibtek]

2007

• David Crandall, Daniel Huttenlocher, "Composite Models of Objects and Scenes for Category Recognition," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007. (Poster, 23.4% acceptance rate) [ Paper] [ bibtek]
• David Crandall, Pedro Felzenszwalb, Daniel Huttenlocher, "Object Recognition by Combining Appearance and Geometry," Toward Category-Level Object Recognition, 2007. [ Paper] [ bibtek] [ Project page]

2006

• Jiebo Luo, David Crandall, "Color Object Detection using Spatial-Color Joint Probability Functions," IEEE Transactions on Image Processing (TIP), 2006. (impact factor = 3.199) [ bibtek]
• David Crandall, Daniel Huttenlocher, "Weakly supervised learning of part-based spatial models for visual object recognition," European Conference on Computer Vision (ECCV), 2006. (Oral, 4.4% acceptance rate) [ Paper] [ bibtek] [ Project page]

2005

• David Crandall, Pedro Felzenszwalb, Daniel Huttenlocher, "Spatial Priors for Part-Based Recognition using Statistical Models," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005. (Oral, 3.7% acceptance rate) [ Paper] [ bibtek] [ Project page]

2004

• David Crandall, Jiebo Luo, "Robust Color Object Detection using Spatial-Color Joint Probability Functions," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2004. (Poster, 23.6% acceptance rate) [ Paper] [ bibtek]

2003

• Jiebo Luo, David Crandall, Amit Singhal, Matthew Boutell, Robert Gray, "Psychophysical study of image orientation perception," Spatial Vision, 2003. (impact factor = 1.037) [ Paper] [ bibtek]
• Jiebo Luo, Amit Singhal, David Crandall, Robert Gray, "A Psychophysical Study of Image Orientation Determination," SPIE Conference on Human Vision and Image Processing, 2003. [ bibtek]

2002

• David Crandall, Sameer Antani, Rangachar Kasturi, "Extraction of special effects caption text events from digital video," International Journal of Document Analysis and Recognition (IJDAR), 2002. (impact factor = 0.800) [ Paper] [ bibtek]

2001

• David Crandall, Rangachar Kasturi, "Robust Detection of Stylized Text Events in Digital Video," IAPR International Conference on Document Analysis and Recognition (ICDAR), 2001. [ Paper] [ bibtek]
• Rangachar Kasturi, Sameer Antani, David Crandall, "A Framework for Reliable Text-Based Indexing of Video," Symposium on Document Image Understanding Technology, 2001. [ Paper] [ bibtek]
• David Crandall, "Extraction of Unconstrained Caption Text from General-Purpose Video," The Pennsylvania State University, 2001. (M.S. Thesis) [ Paper] [ bibtek]

2000

• Sameer Antani, David Crandall, Rangachar Kasturi, "Robust Extraction of Text in Video," IAPR International Conference on Pattern Recognition (ICPR), 2000. [ Paper] [ bibtek]
• Sameer Antani, David Crandall, Anand Narasimamurthy, Vladimir Mariano, Rangachar Kasturi, "Evaluation of Methods for Detection and Localization of Text from Video," IAPR Workshop on Document Analysis Systems, 2000. [ Paper] [ bibtek]

1999

• Ullas Gargi, David Crandall, Sameer Antani, Tarak Gandhi, Ryan Keener, Rangachar Kasturi, "A System for Automatic Text Detection in Video," IAPR International Conference on Document Analysis and Recognition (ICDAR), 1999. [ Paper] [ bibtek]

By Year

2024

• Long-Jing Hsu, Philip B. Stafford, Weslie Khoo, Manasi Swaminathan, Kyrie Jig Amon, Hiroki Sato, Kate Tsui, David J. Crandall, and Selma Sabanovic. “Give it time:” Longitudinal Panels Scaffold Older Adults’ Learning and Robot Co-Design. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024.
• Satoshi Tsutsui, Yanwei Fu, and David J. Crandall. Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 46(3):1455–1463, March 2024. (impact factor = 17.861). [pdf]
• Vibhas K. Vats, Sripad Joshi, David J. Crandall, Md. Alimoor Reza, and Soon-heung Jung. GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2024.
• Xiaomeng Ye, David Leake, Yu Wang, Ziwei Zhao, and David J. Crandall. Network Implementation of CBR: Case Study of a Neural Network K-NN. In International Conference on Case-based Reasoning (ICCBR), 2024.
• Zachary Wilkerson, David Leake, Vibhas Vats, and David J. Crandall. Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. In International Conference on Case-based Reasoning (ICCBR), 2024.
• Kangsan Lee, Jaehyuk Park, Sam Goree, David J. Crandall, and Yong-Yeol Ahn. Social signals predict contemporary art prices better than visual features, particularly in emerging markets. Scientific Reports, May 2024. (impact factor 4.6).
• Xizi Wang, Feng Cheng, and Gedas Bertasius. LoCoNet: Long-Short Context Network for Active Speaker Detection. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
• Ziwei Zhao, Yuchen Wang, and Chuhua Wang. Fusing Personal and Environmental Cues for Identification and Segmentation of First-Person Camera Wearers in Third-Person. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
• Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Triantafyllos Afouras, Kumar Ashutosh, Vijay Baiyya, Siddhant Bansal, Bikram Boote, Eugene Byrne, Zach Chavis, Joya Chen, Feng Cheng, Fu-Jen Chu, Sean Crane, Avijit Dasgupta, Jing Dong, Maria Escobar, Cristhian Forigua, Abrham Gebreselasie, Sanjay Haresh, Jing Huang, Md Mohaiminul Islam, Suyog Jain, Rawal Khirodkar, Devansh Kukreja, Kevin J Liang, Jia-Wei Liu, Sagnik Majumder, Yongsen Mao, Miguel Martin, Effrosyni Mavroudi, Tushar Nagarajan, Francesco Ragusa, Santhosh Kumar Ramakrishnan, Luigi Seminara, Arjun Somayazulu, Yale Song, Shan Su, Zihui Xue, Edward Zhang, Jinxu Zhang, Angela Castillo, Changan Chen, Xinzhu Fu, Ryosuke Furuta, Cristina Gonzalez, Prince Gupta, Jiabo Hu, Yifei Huang, Yiming Huang, Weslie Khoo, Anush Kumar, Robert Kuo, Sach Lakhavani, Miao Liu, Mi Luo, Zhengyi Luo, Brighid Meredith, Austin Miller, Oluwatumininu Oguntola, Xiaqing Pan, Penny Peng, Shraman Pramanick, Merey Ramazanova, Fiona Ryan, Wei Shan, Kiran Somasundaram, Chenan Song, Audrey Southerland, Masatoshi Tateno, Huiyu Wang, Yuchen Wang, Takuma Yagi, Mingfei Yan, Xitong Yang, Zecheng Yu, Shengxin Cindy Zha, Chen Zhao, Ziwei Zhao, Zhifan Zhu, Jeff Zhuo, Pablo Arbelaez, Gedas Bertasius, Dima Damen, Jakob Engel, Giovanni Maria Farinella, Antonino Furnari, Bernard Ghanem, Judy Hoffman, C.V. Jawahar, Richard Newcombe, Hyun Soo Park, James M. Rehg, Yoichi Sato, Manolis Savva, Jianbo Shi, Mike Zheng Shou, and Michael Wray. Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
• David Leake, Zachary Wilkerson, and David J. Crandall. Combining Case-Based Reasoning with Deep Learning: Context and Ongoing Case Feature Learning Research. In AAAI Workshop on Neuro-Symbolic Learning and Reasoning in the Era of Large Language Models, 2024.
• Long-Ling Hsu, Weslie Khoo, Peter Lenon Goshomi, Philip B. Stafford, Manasi Swaminathan, Kate Tsui, David J. Crandall, and Selma Sabanovic. Is Now a Good Time? Opportune Moments for Interacting with an Ikigai Support Robot. In Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024.
• Manasi Swaminathan, Long-Ling Hsu, Min Min Thant, Kyrie Jig Amon, Anna Kim, Kate Tsui, Selma Sabanovic, David J. Crandall, and Weslie Khoo. If [YourName] can code, so can you! End-user robot programming for non-experts. In Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2024.

2023

• Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, and Gedas Bertasius. VindLU: A recipe for Effective Video-and-Language Pretraining. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [pdf]
• Sam Goree, Weslie Khoo, and David Crandall. Correct for Whom? Subjectivity and the Evaluation of Personalized Image Aesthetics Assessment Models. In AAAI Conference on Artificial Intelligence, 2023. (Oral, 19.6% acceptance rate). [pdf]
• Tianfei Zhou, Fatih Porikli, David J. Crandall, Luc Van Gool, and Wenguan Wang. A Survey on Deep Learning Techniques for Video Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023. (impact factor 17.861, accepted, to appear). [pdf]
• Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Yuchen Wang, Ella Atkins, and David J. Crandall. DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45(1):444 – 459, January 2023. (impact factor = 17.861). [pdf]
• Sam Goree, David Crandall, and Norman Su. “It Was Really All About Books:” Speech-like Techno-Masculinity in the Rhetoric of Dot-Com Era Web Design Books. ACM Transactions on Computer-Human Interaction, 30(2):1–27, 2023. (impact factor = 3.147). [pdf]
• Junbo Yin, Jianbing Shen, Xin Gao, David Crandall, and Ruigang Yang. Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), August 2023. (impact factor = 17.861). [pdf]
• Imran Kabir, Shaurya Shubham, Vijayalaxmi Bhimrao Maigur, Mahesh Ravindra Latnekar, Mayank Kumar Raunak, Nikhil Shripad Thakurdesai, David Crandall, and Md Reza. Few-shot segmentation and Semantic Segmentation for Underwater Imagery. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2023.
• Zheng Chen, Zhengming Ding, David Crandall, and Lantao Liu. Polyline Generative Navigable Space Segmentation for Autonomous Visual Navigation. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2023.
• Zachary Wilkerson, Vibhas Vats, Karan Acharya, David Leake, and David Crandall. Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. In International Conference on Case-based Reasoning (ICCBR), 2023. [pdf]
• Long-Jing Hsu, Weslie Khoo, Natasha Randall, Waki Kamino, Swapna Joshi, Hiroki Sato, David Crandall, Kate Tsui, and Selma Sabanovic. Finding Its Voice: Exploring the Influence of Robot Voices on Fit, Social Attributes, and Willingness Among Older Adults in the U.S. and Japan. In IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023. [pdf]
• Jane Yang, Linda Smith, David Crandall, and Chen Yu. Using manual actions to create visual saliency: an outside-in solution to sustained attention and joint attention. In Annual Conference of the Cognitive Science Society (CogSci), 2023.
• Zheng Chen, Zhengming Ding, David J. Crandall, and Lantao Liu. Polyline Generative Navigable Space Segmentation for Autonomous Visual Navigation. IEEE Robotics and Automation Letters (RA-L), April 2023. (impact factor 3.741).
• Sam Goree and David Crandall. Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision. In IEEE CVPR Joint International Third Ego4D and Eleventh EPIC Workshop, 2023. [pdf]
• Weslie Khoo, Long-Jing Hsu, Kyrie Jig Amon, Pranav Vijay Chakilam, Wei-Chu Chen, Zachary Kaufman, Agness Lungu, Hiroki Sato, Erin Seliger, Manasi Swaminathan, Katherine Tsui, David Crandall, and Selma Sabanovic. Spill the Tea: When Robot Conversation Agents Support Well-being for Older Adults. In Companion of the ACM/IEEE International Conference on Human Robot Interaction (HRI), 2023. [pdf]
• David Leake, Zachary Wilkerson, Xiaomeng Ye, and David J. Crandall. Enhancing Case-Based Reasoning with Neural Networks. In Compendium of Neurosymbolic Artificial Intelligence, 387–409, 2023.
• Filippo Menczer, David Crandall, Yong-Yeol Ahn, and Apu Kapadia. Addressing the harms of AI-generated inauthentic content. Nature Machine Intelligence, July 2023. (impact factor = 25.898).
• Long-Jing Hsu, Waki Kamino, Weslie Khoo, Katherine Tsui, David J. Crandall, and Selma Sabanovic. Working Together Toward ikigai: Co-Designing Robots That Can Help Us Achieve Meaning and Purpose in Life. XRDS: Crossroads, 30(1):38–45, 2023.

2022

• Chuhua Wang, Yuchen Wang, Mingze Xu, and David Crandall. Stepwise Goal-Driven Networks for Trajectory Prediction. IEEE Robotics and Automation Letters (RA-L), April 2022. (impact factor = 3.741). [pdf]
• Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, and Jiebo Luo. Zero-Shot Video Object Segmentation with Co-Attention Siamese Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 4(4):2228–2242, April 2022. (impact factor = 17.861).
• Xiankai Lu, Wenguan Wang, Jianbing Shen, David J. Crandall, and Luc Van Gool. Segmenting Objects from Relational Visual Data. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), November 2022. (impact factor = 17.861).
• Zhenhua Chen, Chuhua Wang, and David Crandall. Semantically Stealthy Adversarial Attacks against Segmentation Models. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. (35.0% acceptance rate). [pdf]
• Zehua Zhang and David Crandall. Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. (35.0% acceptance rate). [pdf]
• Satoshi Tsutsui, Xizi Wang, Guangyuan Weng, Yayun Zhang, David Crandall, and Chen Yu. Action Recognition based on Cross-Situational Action-object Statistics. In IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2022. [pdf]
• Xiaomeng Ye, David Leake, and David Crandall. Case Adaptation with Neural Networks: Capabilities and Limitations. In International Conference on Case-based Reasoning (ICCBR), 2022. [pdf]
• David Leake, Zachary Wilkerson, and David Crandall. Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. In International Conference on Case-based Reasoning (ICCBR), 2022. [pdf]
• Xiaomeng Ye, Ziwei Zhao, David Leake, and David Crandall. Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach. In International Conference on Computational Creativity (ICCC), 2022.
• Zehua Zhang, David Crandall, Michael Proulx, Sachin Talathi, and Abhishek Sharma. Can Gaze Inform Egocentric Action Recognition? In ACM Symposium on Eye Tracking Research and Applications (ETRA), 2022. [pdf]
• Vibhas Vats and David Crandall. Controlling the Quality of Distillation in Response-Based Network Compression. In AAAI International Workshop on Practical Deep Learning in the Wild, 2022. [pdf]
• Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Christian Fuegen, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, and Jitendra Malik. Ego4D: Around the World in 3,000 Hours of Egocentric Video. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [pdf]
• Ziwei Zhao, David Leake, Xiaomeng Ye, and David Crandall. Generating Counterfactual Images: Toward a C2C-VAE Approach. In International Conference on Case-based Reasoning Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems, 2022. [pdf]

2021

• Norman Su and David J. Crandall. The Affective Growth of Computer Vision. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (Poster, 23.7% acceptance rate). [pdf]
• Joshua Smith, Md Alimoor Reza, Nathanael Smith, Jianxin Gu, Maha Ibrar, David Crandall, and Sara Skrabalak. Plasmonic Anti-counterfeit Tags with High Encoding Capacity Rapidly Authenticated with Deep Machine Learning. ACS Nano, 15(2):2901 – 2910, February 2021. (impact factor = 14.588).
• Jagpreet Chawla, Nikhil Shripad Thakurdesai, Anuj Balasaheb Godase, Md Alimoor Reza, David J. Crandall, and Soon-Heung Jung. Error Diagnosis of Deep Monocular Depth Estimation Models. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2021. [pdf]
• Xiaomeng Ye, David Leake, Vahid Jalali, and David Crandall. Learning Adaptations for Case-Based Classification: A Neural Network Approach. In International Conference on Case-based Reasoning (ICCBR), 2021. [pdf]
• Zachary Wilkerson, David Leake, and David Crandall. On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. In International Conference on Case-based Reasoning (ICCBR), 2021. [pdf]
• Yayun Zhang, Andrei Amatuni, Ellis Cain, Xizi Wang, David Crandall, and Chen Yu. Statistical learning of verb meaning. In Annual Conference of the Cognitive Science Society (CogSci), 2021. [pdf]
• Ryan Peters, Andrei Amatuni, Sara Schroer, Shujon Naha, David Crandall, and Chen Yu. Are you with me? Modeling joint attention from egocentric vision. In Annual Conference of the Cognitive Science Society (CogSci), 2021. [pdf]
• Andrei Amatuni, Sara Schroer, Ryan Peters, Md Alimoor Reza, Yayun Zhang, David Crandall, and Chen Yu. In-the-Moment Visual Information Determines Learning. In Annual Conference of the Cognitive Science Society (CogSci), 2021. [pdf]
• Sam Goree, Bardia Doosti, David J. Crandall, and Norman Su. Investigating the Homogenization of Web Design: A Mixed-Methods Approach. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2021. (Oral, 26% acceptance rate). [pdf]
• Satoshi Tsutsui, Yanwei Fu, and David J. Crandall. Whose hand is this? Person Identification from Egocentric Hand Gestures. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [pdf]
• Shujon Naha, Qingyang Xiao, Prianka Banik, Md Alimoor Reza, and David J. Crandall. Part Segmentation of Unseen Objects Using Keypoint Guidance. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [pdf]
• Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, and David Crandall. Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features. In IJCAI Workshop on Deep Learning, Case-Based Reasoning, and AutoML: Present and Future Synergies, 2021. [pdf]
• Chia-Fang Chung, Alejandra Ramos, Pei-Ni Chiang, Chien-Chun Wu, Connie Anne Tan, Weslie Khoo, and David Crandall. Computer Vision for Dietary Assessment. In CHI Workshop on Realizing AI in Healthcare: Challenges Appearing in the Wild, 2021. [pdf]
• David Leake, Xiaomeng Ye, and David Crandall. Supporting Case-Based Reasoning with Neural Networks: An Illustration for Case Adaptation. In AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE), 2021. [pdf]
• Yuchen Wang, Mingze Xu, John Paden, Lara Koenig, Geoffrey C. Fox, and David J. Crandall. Deep Tiered Image Segmentation for Detecting Internal Ice Layers in Radar Imagery. In IEEE International Conference on Multimedia and Expo (ICME), 2021. (Oral, 15% acceptance rate). [pdf]

2020

• Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, and Jiebo Luo. Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification. In European Conference on Computer Vision (ECCV), 2020. (27% acceptance rate). [pdf]
• Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, and Chen Yu. A Computational Model of Early Word Learning from the Infant’s Point of View. In Annual Conference of the Cognitive Science Society (CogSci), 2020. (Oral, 22% acceptance rate). [pdf]
• Rakibul Hasan, David Crandall, Mario Fritz, and Apu Kapadia. Automatically Detecting Bystanders in Photos to Reduce Privacy Risks. In IEEE Security and Privacy (Oakland), 2020. [pdf]
• Shujon Naha, Md Alimoor Reza, Chen Yu, and David J. Crandall. Localizing novel attended objects in egocentric views. In British Machine Vision Conference (BMVC), 2020. (Poster, 29.1% acceptance rate). [pdf]
• Lei Yuan, Violet Xiang, David Crandall, and Linda Smith. Learning the generative principles of a symbol system from limited examples. Cognition, 2020. (impact factor = 3.537). [pdf]
• Roberto Hoyle, Luke Stark, Qatrunnada Ismail, David Crandall, Apu Kapadia, and Denise Anthony. Privacy Norms and Preferences for Photos Posted Online. ACM Transactions on Computer-Human Interaction, 2020. (impact factor = 2.227). [pdf]
• David Leake and David Crandall. Bringing Case Based Reasoning to Deep Learning. In International Conference on Case-Based Reasoning Special Track on Challenges and Promises, 2020. [pdf]
• Sam Goree and David Crandall. Studying Empirical Color Harmony in Design. In IEEE Conference on Computer Vision and Pattern Recognition Workshop on Computer Vision for Fashion, Art, and Design, 2020. [pdf]
• Md Alimoor Reza, Kai Chen, Akshay Naik, David J. Crandall, and Soon-Heung Jung. Automatic dense annotation for monocular 3d scene understanding. IEEE Access, 8:68852 – 68865, 2020. (impact factor = 4.098). [pdf]
• Md Alimoor Reza, Zhenhua Chen, and David J. Crandall. Deep Neural Network-based Detection and Verification of Microelectronic Images. Journal of Hardware and Systems Security, 4:44–54, 2020. [pdf]
• Sam Goree, Bardia Doosti, David Crandall, and Norman Su. Yes, websites really are starting to look more similar. The Conversation, 2020. [pdf]
• Ishtiak Zaman and David Crandall. Genetic-GAN: Synthesizing images between two domains by genetic crossover. In European Conference on Computer Vision Workshop on Advances in Manipulation, 2020.
• Shujon Naha, Qingyang Xiao, Prianka Banik, Md Alimoor Reza, and David J. Crandall. Pose-guided knowledge transfer for object part segmentation. In IEEE Conference on Computer Vision and Pattern Recognition Workshop on Visual Learning with Limited Labels, 2020. [pdf]
• Oluwanisola Ibikunle, John Paden, Maryam Rahnemoonfar, David Crandall, and Masoud Yari. Snow Radar Layer Tracking using an Iterative Neural Network Approach. In IEEE International Geoscience and Remote Sensing Symposium, 2020.
• Bardia Doosti, Shujon Naha, Majid Mirbagheri, and David Crandall. HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Poster, 22.1% acceptance rate). [pdf] [project page]
• Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, and Steven Hoi. Learning Video Object Segmentation from Unlabeled Videos. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Poster, 22.1% acceptance rate). [pdf]
• Zehua Zhang, Ashish Tawari, Sujitha Martin, and David Crandall. Interaction Graph for Object Importance Estimation in On-road Driving Videos. In IEEE Conference on Robotics and Automation (ICRA), 2020. (Oral, 42% acceptance rate). [pdf]

2019

• Zehua Zhang, Chen Yu, and David Crandall. A Self Validation Network for Object-Level Human Attention Estimation. In Advances in Neural Information Processing Systems (NeurIPS), 2019. (Poster, 21.6% acceptance rate). [pdf] [project page]
• Jianwei Yang, Zhile Ren, Mingze Xu, Xinlei Chen, David Crandall, Devi Parikh, and Dhruv Batria. Embodied Visual Recognition: Learning to Move for Amodal Perception. In IEEE International Conference on Computer Vision (ICCV), 2019. (Poster, 25.0% acceptance rate). [pdf]
• Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry Davis, and David J. Crandall. Temporal Recurrent Networks for Online Action Detection. In IEEE International Conference on Computer Vision (ICCV), 2019. (Poster, 25.0% acceptance rate). [pdf]
• Yu Yao, Mingze Xu, Chiho Choi, David J. Crandall, Ella M. Atkins, and Behzad Dariush. Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems. In IEEE Conference on Robotics and Automation (ICRA), 2019. (Oral, 44% acceptance rate). [pdf]
• Rakibul Hasan, Yifang Li, Eman Hassan, Kelly Caine, David J. Crandall, Roberto Hoyle, and Apu Kapadia. Can Privacy Be Satisfying? On Improving Viewer Satisfaction for Privacy-Enhanced Photos Using Aesthetic Transforms. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2019. (Oral, 23.8% acceptance rate). [pdf]
• Wenguan Wang, Xiankai Lu, Jianbing Shen, David Crandall, and Ling Shao. Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks. In IEEE International Conference on Computer Vision (ICCV), 2019. (Oral, 25.0% acceptance rate). [pdf]
• Yu Yao, Mingze Xu, Yuchen Wang, David Crandall, and Ella Atkins. Unsupervised Traffic Accident Detection in First-Person Videos. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2019. (Oral, 45.0% acceptance rate). [pdf]
• Md Alimoor Reza, Akshay Naik, Kai Chen, and David Crandall. Automatic Annotation for Semantic Segmentation in Indoor Scenes. In IEEE International Conference on Intelligent Robots and Systems (IROS), 2019. (Oral, 45.0% acceptance rate). [pdf]
• Jangwon Lee, Bardia Doosti, Yupeng Gu, David Cartledge, David J. Crandall, and Christopher Raphael. Observing Pianist Accuracy and Form with Computer Vision. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2019. (Poster+Oral, 39% acceptance rate). [pdf]
• Suzanne Menzel, Katie Siek, and David Crandall. Hello Research! Developing an Intensive Research Experience for Undergraduate Women. In ACM Technical Symposium on Computer Science Education (SIGCSE), 2019. (Oral, 34% acceptance rate). [pdf] [project page]
• Jeremy I. Borjon, Sara E. Schroer, Sven Bambach, Lauren K. Slone, Drew H. Abney, David J. Crandall, and Linda B. Smith. A View of Their Own: Capturing the Egocentric View of Infants and Toddlers with Head-Mounted Cameras. Journal of Visualized Experiments, 2019. (impact factor = 1.325).
• Hadar Karmazyn Raz, Drew H. Abney, David Crandall, Chen Yu, and Linda Smith. How do infants start learning object names in a sea of clutter? In Annual Conference of the Cognitive Science Society (CogSci), 2019. [pdf]
• Aniruddha M. Godbole and David J. Crandall. Empowering Borrowers in their Choice of Lenders: Decoding Service Quality from Customer Complaints. In ACM International Web Science Conference (WebSci), 2019. (Oral, 34.2% acceptance rate). [pdf]
• Katie Spoon, David Crandall, and Katie Siek. Towards Detecting Dyslexia in Children’s Handwriting Using Neural Networks. In ICML Workshop on AI for Social Good, 2019. Best poster award. [pdf] [project page]
• Satoshi Tsutsui, Dian Zhi, Md Alimoor Reza, David Crandall, and Chen Yu. Active Object Manipulation Facilitates Visual Object Learning: An Egocentric Vision Study. In IEEE CVPR Workshop on Egocentric Perception, Interaction, and Computing (EPIC), 2019. [pdf]
• Zhenhua Chen, Chuhua Wang, Tiancong Zhao, and David Crandall. Generalized Capsule Networks with Trainable Routing Procedure. In International Conference on Machine Learning Workshop on Generalization, 2019. [pdf]
• Tousif Ahmed, Rakibul Hasan, Kay Connelly, David Crandall, and Apu Kapadia. Conveying Situational Information to People with Visual Impairments. In CHI Workshop on Addressing the Challenges of Situationally-Induced Impairments and Disabilities in Mobile Interaction, 2019. [pdf]
• David Crandall. Artificial Intelligence and Manufacturing. In Smart Factories: Issues of Information Governance, 2019. [pdf]
• Geoffrey Fox, Judy Qiu, David Crandall, Gregor Von Laszewski, Oliver Beckstein, John Paden, Ioannis Paraskevakos, Shantenu Jha, Fusheng Wang, Madhav Marathe, Anil Vullikanti, and Thomas Cheatham. Contributions to High-Performance Big Data Computing. In Future Trends of HPC in a Disruptive Scenario, volume 34, 34 – 81, 2019. [pdf]
• Victor Berger, Mingze Xu, Mohanad Al-Ibadi, Shane Chu, David Crandall, John Paden, and Geoffrey Fox. Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 12(9):3272 – 3285, 2019. (impact factor = 3.392). [pdf]
• Noam Levin, Saleem Ali, David Crandall, and Salit Kark. World Heritage in danger: Big data and remote sensing can help protect sites in conflict zones. Global Environmental Change, 55:97–104, 2019. (impact factor = 6.371).
• Satoshi Tsutsui, Yanwei Fu, and David Crandall. Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition. In Advances in Neural Information Processing Systems (NeurIPS), 2019. (Poster, 21.6% acceptance rate). [pdf] [project page]

2018

• Sven Bambach, David Crandall, Linda Smith, and Chen Yu. Toddler-Inspired Visual Object Learning. In Advances in Neural Information Processing Systems (NeurIPS), 2018. (Poster, 20.8% acceptance rate). [pdf]
• Mingze Xu, Chenyou Fan, Yuchen Wang, Michael Ryoo, and David Crandall. Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos. In European Conference on Computer Vision (ECCV), 2018. (Poster). [pdf] [project page]
• Rakibul Hasan, Eman Hassan, Yifang Li, Kelly Caine, David J. Crandall, Roberto Hoyle, and Apu Kapadia. Viewer Experience of Obscuring Scene Elements in Photos to Enhance Privacy. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2018. (Oral, 25.7% acceptance rate). [pdf]
• Ashwin Vijayakumar, Michael Cogswell, Ramprasaath Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra. Diverse Beam Search for Improved Description of Complex Scenes. In AAAI Conference on Artificial Intelligence, 2018. (Poster, 24.6% acceptance rate). [pdf]
• Satoshi Tsutsui, Sven Bambach, David Crandall, and Chen Yu. Estimating Head Motion from Egocentric Vision. In ACM International Conference on Multimodal Interaction (ICMI), 2018. [pdf]
• Zehua Zhang, Sven Bambach, David Crandall, and Chen Yu. From Coarse Attention to Fine-Grained Gaze: A Two-stage 3D Fully Convolutional Network for Predicting Eye Gaze in First Person Video. In British Machine Vision Conference (BMVC), 2018. (Oral, 4.3% acceptance rate). [pdf] [project page]
• Mingze Xu, Aidean Sharghi, Xin Chen, and David Crandall. Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. (40% acceptance rate). [pdf]
• Mingze Xu, Chenyou Fan, John Paden, Geoffrey Fox, and David Crandall. Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. (40% acceptance rate). [pdf]
• Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Victor Berger, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, and Wesley Van Wychen. Crossover Analysis and Automated Layer-Tracking Assessment of the Extracted DEM of the Basal Topography of the Canadian Arctic Archipelago Ice-Cap. In IEEE Radar Conference, 2018. [pdf]
• Victor Berger, Mingze Xu, David Crandall, John Paden, and Geoffrey Fox. Automated Tracking of 2d and 3d Ice Radar Imagery using Viterbi and TRW-S. In IEEE International Geoscience and Remote Sensing Symposium, 2018.
• Satoshi Tsutsui, Tommi Kerola, Shunta Saito, and David Crandall. Minimizing Supervision for Free-space Segmentation. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Autonomous Driving (WAD), 2018. [pdf]
• Jangwon Lee, Haodan Tan, David Crandall, and Selma Sabanovic. Forecasting Hand Gestures for Human-Drone Interaction. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 2018. (Late-breaking Report). [pdf]
• Bo-chiuan Chen, Dong-Chul Seo, Hsien-Chang Lin, and David Crandall. A Framework for Estimating Sleep Timing from Digital Footprints. BMJ Innovations, 2018. (impact factor = 2.899).
• Chenyou Fan, Zehua Zhang, and David Crandall. Deepdiary: Lifelogging image captioning and summarization. Journal of Visual Communication and Image Representation, 55:40–55, August 2018. (impact factor = 2.164). [project page]
• Noam Levin, Saleem Ali, and David Crandall. Utilizing remote sensing and big data to quantify conflict intensity: The Arab Spring as a case study. Applied Geography, 2018. (impact factor = 2.56). [pdf]

2017

• Scott Workman, Menghua Zhai, David Crandall, and Nathan Jacobs. A unified model for near and remote sensing. In IEEE International Conference on Computer Vision (ICCV), 2017. (Poster, 28% acceptance rate). [pdf] [project page]
• Chenyou Fan, Jangwon Lee, Mingze Xu, Krishna Kumar Singh, Yong Jae Lee, David Crandall, and Michael Ryoo. Identifying first-person camera wearers in third-person videos. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (Poster, 29.0% acceptance rate). [pdf] [project page]
• Wen Chen, David Crandall, and Norman Su. Understanding the Aesthetic Evolution of Websites: Towards a Notion of Design Periods. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2017. (Oral, 25.0% acceptance rate). [pdf]
• Mingze Xu, David J. Crandall, Geoffrey C. Fox, and John D. Paden. Automatic estimation of ice bottom surfaces from radar imagery. In IEEE International Conference on Image Processing (ICIP), 2017. (Oral, 45.0% acceptance rate). [pdf]
• Satoshi Tsutsui and David J. Crandall. A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks. In IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017. [pdf] [project page]
• Bardia Doosti, David J. Crandall, and Norman Makoto Su. A deep study into the history of web design. In ACM International Web Science Conference (WebSci), 2017. (Oral, 35.3% acceptance rate). [pdf] [project page]
• Sven Bambach, David Crandall, Linda Smith, and Chen Yu. An Egocentric Perspective on Active Vision and Visual Object Learning in Toddlers. In IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2017. (Oral, 37.1% acceptance rate). [pdf]
• Eman Hassan, Rakibul Hasan, Patrick Shaffer, David Crandall, and Apu Kapadia. Cartooning for enhanced privacy in lifelogging and streaming video. In IEEE Conference on Computer Vision and Pattern Recognition Workshop on Computer Vision Challenges and Opportunities for Privacy and Security (CVPR CV-COPS), 2017. [pdf]
• Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David Crandall, and Robert Templeman. Addressing supply chain risks of microelectronic devices through computer vision. In IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2017. [pdf]
• Sven Bambach, Zehua Zhang, David Crandall, and Chen Yu. Exploring inter-observer differences in first-person object views using deep learning models. In IEEE International Conference on Computer Vision Workshop on Mutual Benefits of Cognitive and Computer Vision, 2017. [pdf]
• Jangwon Lee, Jingya Wang, David Crandall, Selma Sabanovic, and Geoffrey Fox. Real-Time, Cloud-based Object Detection for Unmanned Aerial Vehicles. In IEEE Robotic Computing, 2017. (Oral). [pdf]
• Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, and Wesley Van Wychen. DEM Extraction of the Basal Topography of the Canadian Archipelago Ice Caps via 2d automated layer-tracking. In IEEE International Geoscience and Remote Sensing Symposium, 2017. (Oral). [pdf]
• Satoshi Tsutsui, Guilin Meng, Xiaohui Yao, David Crandall, and Ying Ding. Analyzing figures of brain images from Alzheimer’s Disease Papers. In iConference, 2017. [pdf]
• Tousif Ahmed, Roberto Hoyle, Patrick Shaffer, Kay Connelly, David Crandall, and Apu Kapadia. Understanding the Physical Safety, Security, and Privacy Concerns of People with Visual Impairments. IEEE Internet Computing, 21(3):56 – 63, 2017. (impact factor = 2.0).
• Johan Bollen, David Crandall, Damion Junk, Ying Ding, and Katy Borner. An efficient system to fund science: from proposal review to peer-to-peer distributions. Scientometrics, 110(1):521–528, 2017. (impact factor = 2.084).
• Eman T. Hassan and David J. Crandall. A Study of Cross-domain Generative Models applied to Cartoon Series. Technical Report, arXiv:1710.00755, 2017. [pdf]
• Satoshi Tsutsui and David Crandall. Using Artificial Tokens to Control Languages for Multilingual Image Caption Generation. Technical Report, arXiv:1706.06275, 2017. [pdf]
• Satoshi Tsutsui and David J. Crandall. A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks. Technical Report, arXiv1708.03035, 2017. [pdf]
• Scott Workman, Menghua Zhai, David Crandall, and Nathan Jacobs. A unified model for near and remote sensing. Technical Report, arXiv:1708.03035, 2017. [pdf]

2016

• Mohammed Korayem, Robert Templeman, Dennis Chen, David Crandall, and Apu Kapadia. Enhancing Lifelogging Privacy by Detecting Screens. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2016. Honorable Mention Award. (CHI Note, 23.4% acceptance rate). [pdf] [project page]
• Sven Bambach, David Crandall, Linda Smith, and Chen Yu. Active Viewing in Toddlers Facilitates Visual Object Learning: An Egocentric Vision Approach. In Annual Conference of the Cognitive Science Society (CogSci), 2016. (Oral, 34% acceptance rate). [pdf]
• Jingya Wang, Mohammed Korayem, Saul Blanco, and David Crandall. Tracking Natural Events through Social Media and Computer Vision. In ACM International Conference on Multimedia (MM), 2016. [pdf] [project page]
• Sven Bambach, Linda Smith, David Crandall, and Chen Yu. Objects in the Center: How the Infant’s Body Constrains Infant Scenes. In IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2016. Best paper award. (Oral, 33.7% acceptance rate). [pdf]
• Chenyou Fan and David Crandall. DeepDiary: Automatically Captioning Lifelogging Image Streams. In European Conference on Computer Vision International Workshop on Egocentric Perception, Interaction, and Computing (EPIC), 2016. [pdf] [project page]
• David Crandall, Yunpeng Li, Stefan Lee, and Daniel Huttenlocher. Recognizing landmarks in large-scale social image collections. In Visual Analysis and Geolocalization of Large Scale Imagery, 2016. [pdf]
• Tousif Ahmed, Patrick Shaffer, Kay Connelly, David Crandall, and Apu Kapadia. Addressing Physical Safety, Security, and Privacy for People with Visual Impairments. In USENIX Symposium on Usable Privacy and Security (SOUPS), 2016. (Oral, 27.8% acceptance rate). [pdf]
• Tousif Ahmed, Roberto Hoyle, Patrick Shaffer, Kay Connelly, David Crandall, and Apu Kapadia. Considering Privacy Implications of Assistive Devices for People with Visual Impairments. In CHI Workshop on Interactive Systems in Healthcare (WISH), 2016.
• Kathy Tang and David Crandall. Applying Deep Learning to Improve Maritime Situational Awareness. In ACM International Conference on Knowledge Discovery and Data Mining Workshop on Large-scale Deep Learning for Data Mining, 2016.
• Mohammed Korayem, Khalifeh Aljadda, and David Crandall. Sentiment/Subjectivity Analysis Survey for Languages other than English. Social Network Analysis and Mining, 2016.
• Noam Levin, David Crandall, and Salit Kark. Scale matters: differences between local, regional, and global analyses (letter to the editor). Ecological Applications, 26(7):2359–2362, December 2016. (impact factor = 4.126).
• Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David Crandall, and Dhruv Batra. Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles. In Advances in Neural Information Processing Systems (NeurIPS), 2016. (Poster, 22.7% acceptance rate). [pdf]
• Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra. Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models. Technical Report, arXiv 1610.02424, 2016. [pdf]
• Chenyou Fan and David Crandall. DeepDiary: Automatic caption generation for lifelogging image streams. Technical Report, arXiv 1606.07839, 2016. [pdf]

2015

• Sven Bambach, Stefan Lee, David Crandall, and Chen Yu. Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions. In IEEE International Conference on Computer Vision (ICCV), 2015. (Poster, 30.3% acceptance rate). [pdf] [project page]
• Stefan Lee, Nicolas Maisonneuve, David Crandall, Alexei Efros, and Josef Sivic. Linking past to present: Discovering style in two centuries of architecture. In IEEE International Conference on Computational Photography (ICCP), 2015. (Oral, 24% acceptance rate). [pdf] [project page]
• Roberto Hoyle, Robert Templeman, Denise Anthony, David Crandall, and Apu Kapadia. Sensitive Lifelogs: A Privacy Analysis of Photos from Wearable Cameras. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2015. (CHI Note). [pdf]
• Sven Bambach, David Crandall, and Chen Yu. Viewpoint Integration for Hand-Based Recognition of Social Interactions from a First-Person View. In ACM International Conference on Multimodal Interaction (ICMI), 2015. (Poster, 41% acceptance rate). [pdf]
• Tousif Ahmed, Roberto Hoyle, Kay Connelly, David Crandall, and Apu Kapadia. Privacy Concerns and Behaviors of People with Visual Impairments. In ACM CHI Conference on Human Factors in Computing Systems (CHI), 2015. (Full paper, 23% acceptance rate). [pdf]
• Stefan Lee, Haipeng Zhang, and David Crandall. Predicting Geo-informative Attributes in Large-scale Image Collections using Convolutional Neural Networks. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. (Oral and poster, 36.7% acceptance rate). [pdf] [project page]
• Roberto Hoyle, Apu Kapadia, and David Crandall. Challenges in Running Wearable Camera-Related User Studies. In ACM Conference on Computer-Supported Cooperative Work and Social Computing Workshop on The Future of Networked Privacy: Challenges and Opportunities, 2015.
• Stefan Lee, Senthil Purushwalkam, Michael Cogswell, David Crandall, and Dhruv Batra. Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks. Technical Report, arXiv 1511.06314, 2015. [pdf]
• Supun Kamburugamuve, Hengjing He, Geoffrey Fox, and David Crandall. Cloud-based parallel implementation of SLAM for mobile robots. In International Supercomputing Conference (ISC) Cloud & Big Data Conference, 2015.
• Kun Duan, Dhruv Batra, and David Crandall. Human pose estimation through composite multi-layer models. Signal Processing, 110:15–26, May 2015. (impact factor = 2.238). [pdf] [project page]
• Noam Levin, Salit Kark, and David Crandall. Where have all the people gone? Enhancing global conservation using night lights and social media. Ecological Applications, 25(8):2153–2167, December 2015. (impact factor = 4.126). [pdf]

2014

• Stefan Lee, Sven Bambach, David Crandall, John M. Franchak, and Chen Yu. This Hand is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video. In IEEE Conference on Computer Vision and Pattern Recognition Workshop on Egocentric Vision, 2014. Best paper award winner. (Oral). [pdf]
• Robert Templeman, Roberto Hoyle, David Crandall, and Apu Kapadia. Reactive Security: Responding to Visual Stimuli from Wearable Cameras. In Ubicomp Workshop on Usable Privacy and Security for Wearable and Domestic Ubiquitous Devices (UPSIDE), 2014. [pdf]
• Johan Bollen, David Crandall, Damion Junk, Ying Ding, and Katy Borner. From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review. EMBO Reports, 15:131–133, 2014. (impact factor = 7.189). [pdf]
• Kun Duan, David Crandall, and Dhruv Batra. Multimodal Learning in Loosely-organized Web Images. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (Poster, 29.9% acceptance rate). [pdf]
• Robert Templeman, Mohammed Korayem, David Crandall, and Apu Kapadia. PlaceAvoider: Steering First-Person Cameras away from Sensitive Spaces. In Network and Distributed System Security Symposium (NDSS), 2014. (Oral, 18.6% acceptance rate). [pdf]
• Stefan Lee, Jerome Mitchell, David Crandall, and Geoffrey C. Fox. Estimating Bedrock and Surface Layer Boundaries and Confidence Intervals in Ice Sheet Radar Imagery using MCMC. In IEEE International Conference on Image Processing (ICIP), 2014. (Oral, 44% acceptance rate). [pdf] [project page]
• Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, and Apu Kapadia. Privacy Behaviors of Lifeloggers using Wearable Cameras. In ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2014. (Oral, 20.7% acceptance rate). [pdf]
• Sven Bambach, John Franchak, David Crandall, and Chen Yu. Detecting Hands in Children’s Egocentric Views to Understand Embodied Attention during Social Interaction. In Annual Conference of the Cognitive Science Society (CogSci), 2014. (Oral, 41.0% acceptance rate). [pdf]
• Kun Duan, Luca Marchesotti, and David Crandall. Vehicle Recognition with Constrained Multiple Instance SVMs. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2014. (Oral and poster, 40% acceptance rate). [pdf]
• Haipeng Zhang, Zhixian Yan, Jun Yang, Emmanuel Munguia Tapia, and David Crandall. mFingerprint: Privacy-preserving user modeling with multimodal mobile device footprints. In International Conference on Social Computing, Behavior-Cultural Modeling, & Prediction (SBP), 2014. (Oral, 24% acceptance rate). [pdf]
• Johan Bollen, David Crandall, Damion Junk, Ying Ding, and Katy Borner. Response: “Why we still need grant peer review”. EMBO Reports, 15(5):467, May 2014. (impact factor = 7.189).
• Mohammed Korayem, Robert Templeman, Dennis Chen, David Crandall, and Apu Kapadia. ScreenAvoider: Protecting Computer Screens from Ubiquitous Cameras. Technical Report, arXiv 1412.0008, 2014. [pdf]

2013

• Jingya Wang, Mohammed Korayem, and David Crandall. Observing the natural world with Flickr. In International Conference on Computer Vision Workshop on Computer Vision for Converging Perspectives, 2013. Best paper award winner. (Oral). [pdf]
• Jerome E. Mitchell, David Crandall, Geoffrey Fox, and John Paden. Automatic Near Surface Estimation from Snow Radar Imagery. In IEEE International Geoscience and Remote Sensing Symposium, 2013. (Oral). [pdf]
• Jerome E. Mitchell, David Crandall, Geoffrey C. Fox, Maryam Rahnemoonfar, and John D. Paden. A Semi-Automatic Approach for Estimating Bedrock and Surface Layers from Multichannel Coherent Radar Depth Sounder Imagery. In SPIE Conference on Remote Sensing, 2013. (Oral).
• David Crandall, Andrew Owens, Noah Snavely, and Daniel Huttenlocher. SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 35(12):2841–2853, December 2013. (impact factor = 4.795). [pdf] [project page]
• Robert Templeman, Zahidur Rahman, David Crandall, and Apu Kapadia. PlaceRaider: Virtual Theft in Physical Spaces with Smartphones. In Network and Distributed System Security Symposium (NDSS), 2013. (Oral, 18% acceptance rate). [pdf] [project page]
• Sven Bambach, David Crandall, and Chen Yu. Understanding Embodied Visual Attention in Child-Parent Interaction. In IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), 2013. (Oral, 33% acceptance rate). [pdf]
• Mohammed Korayem and David Crandall. De-anonymizing users across heterogeneous social computing platforms. In AAAI International Conference on Weblogs and Social Media (ICWSM), 2013. (Poster). [pdf]
• Haipeng Zhang, Nish Parikh, Gyanit Singh, and Neel Sundaresan. Chelsea Won, and You Bought a T-shirt: Characterizing the Interplay Between Twitter and E-Commerce. In ASONAM, 2013. [pdf]

2012

• Mohammed Korayem, Abdallah A. Mohamed, David Crandall, and Roman V. Yampolskiy. Learning visual features for the Avatar Captcha Recognition Challenge. In International Conference on Machine Learning Applications (ICMLA), 2012. [pdf]
• Mohammed Korayem, Abdallah A. Mohamed, David Crandall, and Roman V. Yampolskiy. Solving Avatar Captchas automatically. In International Conference on Advanced Machine Learning Technologies and Applications, 2012. (Oral). [pdf]
• Mohammed Korayem, David Crandall, and Muhammad Abdul-Mageed. Subjectivity and Sentiment Analysis of Arabic: A Survey. In International Conference on Advanced Machine Learning Technologies and Applications, 2012. (Poster). [pdf]
• David Crandall and Noah Snavely. Modeling people and places with internet photo collections. Communications of the ACM (CACM), 55(6):52–60, 2012. (impact factor = 2.51) Also appeared in ACM Queue magazine. [pdf]
• Kun Duan, Devi Parikh, David Crandall, and Kristen Grauman. Discovering Localized Attributes for Fine-grained Recognition. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012. (Poster, 26% acceptance rate). [pdf] [project page]
• Haipeng Zhang, Mohammed Korayem, David Crandall, and Gretchen LeBuhn. Mining Photo-sharing Websites to Study Ecological Phenomena. In International World Wide Web Conference (WWW), 2012. (Oral, 12% acceptance rate). [pdf] [project page]
• Kun Duan, Dhruv Batra, and David Crandall. A Multi-layer Composite Model for Human Pose Estimation. In British Machine Vision Conference (BMVC), 2012. (Poster, 32% acceptance rate). [pdf]
• David Crandall, Geoffrey Fox, and John Paden. Layer-finding in radar echograms using probabilistic graphical models. In IAPR International Conference on Pattern Recognition (ICPR), 2012. (Oral, 15% acceptance rate). [pdf] [project page]
• Haipeng Zhang, Mohammed Korayem, Erkang You, and David Crandall. Beyond Co-occurrence: Discovering and Visualizing Tag Relationships from Geo-spatial and Temporal Similarities. In ACM International Conference on Web Search and Data Mining (WSDM), 2012. (Oral, 8.3% acceptance rate). [pdf] [project page]

2011

• David Crandall, Andrew Owens, Noah Snavely, and Daniel Huttenlocher. Discrete-Continuous Optimization for Large-scale Structure from Motion. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. Best paper runner-up. (Oral, 3.5% acceptance rate). [pdf] [project page]
• David Crandall and Noah Snavely. Networks of Landmarks, Photos, and People. Leonardo, 44(3):240–243, 2011. [pdf]

2010

• David Crandall, Lars Backstrom, Daniel Cosley, Siddharth Suri, Daniel Huttenlocher, and Jon Kleinberg. Inferring Social Ties from Geographic Coincidences. Proceedings of the National Academy of Sciences (PNAS), 107(52):22436–22441, 2010. (impact factor = 9.737). [pdf]

2009

• Yunpeng Li, David Crandall, and Daniel Huttenlocher. Landmark Classification in Large-scale Image Collections. In IEEE International Conference on Computer Vision (ICCV), 2009. (Poster, 23.2% acceptance rate). [pdf]
• David Crandall, Lars Backstrom, Daniel Huttenlocher, and Jon Kleinberg. Mapping the World’s Photos. In International World Wide Web Conference (WWW), 2009. Best paper honorable mention. (Oral, 13% acceptance rate). [pdf] [project page]

2008

• David Crandall, Daniel Cosley, Daniel Huttenlocher, Jon Kleinberg, and Sid Suri. Feedback Effects between Similarity and Social Influence in Online Communities. In ACM International Conference on Knowledge Discovery and Data Mining (KDD), 2008. (Oral, 18.6% acceptance rate). [pdf]

2007

• David Crandall and Daniel Huttenlocher. Composite Models of Objects and Scenes for Category Recognition. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007. (Poster, 23.4% acceptance rate). [pdf]
• David Crandall, Pedro Felzenszwalb, and Daniel Huttenlocher. Object Recognition by Combining Appearance and Geometry. In Toward Category-Level Object Recognition, 2007. [pdf] [project page]

2006

• Jiebo Luo and David Crandall. Color Object Detection using Spatial-Color Joint Probability Functions. IEEE Transactions on Image Processing (TIP), 15(6):1443–1453, 2006. (impact factor = 3.199).
• David Crandall and Daniel Huttenlocher. Weakly supervised learning of part-based spatial models for visual object recognition. In European Conference on Computer Vision (ECCV), 2006. (Oral, 4.4% acceptance rate). [pdf] [project page]

2005

• David Crandall, Pedro Felzenszwalb, and Daniel Huttenlocher. Spatial Priors for Part-Based Recognition using Statistical Models. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005. (Oral, 3.7% acceptance rate). [pdf] [project page]

2004

• David Crandall and Jiebo Luo. Robust Color Object Detection using Spatial-Color Joint Probability Functions. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2004. (Poster, 23.6% acceptance rate). [pdf]

2003

• Jiebo Luo, David Crandall, Amit Singhal, Matthew Boutell, and Robert Gray. Psychophysical study of image orientation perception. Spatial Vision, 16(5):429–456, 2003. (impact factor = 1.037). [pdf]
• Jiebo Luo, Amit Singhal, David Crandall, and Robert T. Gray. A Psychophysical Study of Image Orientation Determination. In SPIE Conference on Human Vision and Image Processing, 2003.
• David Crandall. Initial candidate detection for lung nodule segmentation. Technical Report, Eastman Kodak Company, Rochester, NY, 2003.
• David Crandall. RegionGT: A segmentation-based ground truth tool. Technical Report, Eastman Kodak Company, Rochester, NY, 2003.
• David Crandall and Jiebo Luo. Compound Color Object Detection using Spatial-Color Joint Probability Functions. Technical Report, Eastman Kodak Company, Rochester, NY, 2003.

2002

• David Crandall, Sameer Antani, and Rangachar Kasturi. Extraction of special effects caption text events from digital video. International Journal of Document Analysis and Recognition (IJDAR), 5(2-3):138–157, 2002. (impact factor = 0.800). [pdf]
• David Crandall and Jiebo Luo. AREA 3.5: Improved Automatic Red Eye Reduction Algorithm based on Improved Segmentation. Technical Report 330555Y, Eastman Kodak Company, Rochester, NY, 2002.
• David Crandall and Jiebo Luo. Shape-based Segmentation for Detecting Articulated Human Figures in Images. Technical Report 328988D, Eastman Kodak Company, Rochester, NY, 2002.
• Jiebo Luo, David Crandall, and Amit Singhal. A psychophysical study of image orientation perception. Technical Report 331287B, Eastman Kodak Company, Rochester, NY, 2002.
• David Crandall. A C++ wavelet decomposition library in IEM. Technical Report 331056F, Eastman Kodak Company, Rochester, NY, 2002.
• David Crandall. A neural network library in C++, and rudiments of an abstract classifier class. Technical Report 331055E, Eastman Kodak Company, Rochester, NY, 2002.
• David Crandall. Further lessons learned from the WOO2.1 whole-order orientation algorithm. Technical Report 329189V, Eastman Kodak Company, Rochester, NY, 2002.
• David Crandall. Guide to training, testing, and using the WOO2.1 whole-order orientation algorithm. Technical Report 329190P, Eastman Kodak Company, Rochester, NY, 2002.

2001

• Rangachar Kasturi, Sameer Antani, and David Crandall. A Framework for Reliable Text-Based Indexing of Video. In Symposium on Document Image Understanding Technology, 2001. [pdf]
• David Crandall and Rangachar Kasturi. Robust Detection of Stylized Text Events in Digital Video. In IAPR International Conference on Document Analysis and Recognition (ICDAR), 2001. [pdf]

2000

• Sameer Antani, David Crandall, Anand Narasimamurthy, Vladimir Y. Mariano, and Rangachar Kasturi. Evaluation of Methods for Detection and Localization of Text from Video. In IAPR Workshop on Document Analysis Systems, 2000. [pdf]
• Sameer Antani, David Crandall, and Rangachar Kasturi. Robust Extraction of Text in Video. In IAPR International Conference on Pattern Recognition (ICPR), 2000. [pdf]
• S. Antani, David Crandall, V. Mariano, A. Narasimhamurthy, and R. Kasturi. Reliable Extraction of Text in Video. Technical Report CSE-00-022, Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 2000.

1999

• Ullas Gargi, David Crandall, Sameer Antani, Tarak Gandhi, Ryan Keener, and Rangachar Kasturi. A System for Automatic Text Detection in Video. In IAPR International Conference on Document Analysis and Recognition (ICDAR), 1999. [pdf]
• S. Antani, U. Gargi, David Crandall, T. Gandhi, and R. Kasturi. Extraction of Text in Video. Technical Report CSE-99-016, Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 1999.