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Social media mining

A unified model for near and remote sensing
Scott Workman, Menghua Zhai, David Crandall, Nathan Jacobs
ICCV 2017
A deep study into the history of web design
Bardia Doosti, David Crandall, Norman Makoto Su
WEBSCI 2017
Tracking Natural Events through Social Media and Computer Vision
Jingya Wang, Mohammed Korayem, Saul Blanco, David Crandall
ACMMM 2016
Where have all the people gone? Enhancing global conservation using night lights and social media
Noam Levin, Salit Kark, David Crandall
Ecological Applications 2015
Linking past to present: Discovering style in two centuries of architecture
Stefan Lee, Nicolas Maisonneuve, David Crandall, Alexei Efros, Josef Sivic
ICCP 2015
Multimodal Learning in Loosely-organized Web Images
Kun Duan, David Crandall, Dhruv Batra
CVPR 2014
SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion
David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher
PAMI 2013
Observing the natural world with Flickr
Jingya Wang, Mohammed Korayem, David Crandall
ICCV CVCP Workshop 2013
Best paper award!
Modeling people and places with internet photo collections
David Crandall, Noah Snavely
CACM 2012
Mining Photo-sharing Websites to Study Ecological Phenomena
Haipeng Zhang, Mohammed Korayem, David Crandall, Gretchen LeBuhn
WWW 2012
Networks of Landmarks, Photos, and People
David Crandall, Noah Snavely
Leonardo 2011
Discrete-Continuous Optimization for Large-scale Structure from Motion
David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher
CVPR 2011
Best paper runner-up!
Mapping the World's Photos
David Crandall, Lars Backstrom, Daniel Huttenlocher, Jon Kleinberg
WWW 2009
Best paper honorable mention!

Egocentric computer vision

HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation
Bardia Doosti, Shujon Naha, Majid Mirbagheri, David Crandall
CVPR 2020
Interaction Graph for Object Importance Estimation in On-road Driving Videos
Zehua Zhang, Ashish Tawari, Sujitha Martin, David Crandall
ICRA 2020
A Self Validation Network for Object-Level Human Attention Estimation
Zehua Zhang, Chen Yu, David Crandall
NeurIPS 2019
Embodied Visual Recognition: Learning to Move for Amodal Perception
Jianwei Yang, Zhile Ren, Mingze Xu, Xinlei Chen, David Crandall, Devi Parikh, Dhruv Batria
ICCV 2019
Temporal Recurrent Networks for Online Action Detection
Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry Davis, David Crandall
ICCV 2019
Unsupervised Traffic Accident Detection in First-Person Videos
Yu Yao, Mingze Xu, Yuchen Wang, David Crandall, Ella Atkins
IROS 2019
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems
Yu Yao, Mingze Xu, Chiho Choi, David Crandall, Ella Atkins, Behzad Dariush
ICRA 2019
Deepdiary: Lifelogging image captioning and summarization
Chenyou Fan, Zehua Zhang, David Crandall
JVCI 2018
Estimating Head Motion from Egocentric Vision
Satoshi Tsutsui, Sven Bambach, David Crandall, Chen Yu
ICMI 2018
Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos
Mingze Xu, Chenyou Fan, Yuchen Wang, Michael Ryoo, David Crandall
ECCV 2018
Identifying first-person camera wearers in third-person videos
Chenyou Fan, Jangwon Lee, Mingze Xu, Krishna Kumar Singh, Yong Jae Lee, David Crandall, Michael Ryoo
CVPR 2017
Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions
Sven Bambach, Stefan Lee, David Crandall, Chen Yu
ICCV 2015
This Hand is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video
Stefan Lee, Sven Bambach, David Crandall, John Franchak, Chen Yu
CVPR Egovision Workshop 2014
Best paper award!

Object recognition

Learning Video Object Segmentation from Unlabeled Videos
Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, Steven Hoi
CVPR 2020
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
Satoshi Tsutsui, Yanwei Fu, David Crandall
NeurIPS 2019
Toddler-Inspired Visual Object Learning
Sven Bambach, David Crandall, Linda Smith, Chen Yu
NeurIPS 2018
Recognizing landmarks in large-scale social image collections
David Crandall, Yunpeng Li, Stefan Lee, Daniel Huttenlocher
Visual Analysis and Geolocalization of Large Scale Imagery 2016
Human pose estimation through composite multi-layer models
Kun Duan, Dhruv Batra, David Crandall
Signal Processing 2015
Vehicle Recognition with Constrained Multiple Instance SVMs
Kun Duan, Luca Marchesotti, David Crandall
WACV 2014
Discovering Localized Attributes for Fine-grained Recognition
Kun Duan, Devi Parikh, David Crandall, Kristen Grauman
CVPR 2012
Composite Models of Objects and Scenes for Category Recognition
David Crandall, Daniel Huttenlocher
CVPR 2007
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Color Object Detection using Spatial-Color Joint Probability Functions
Jiebo Luo, David Crandall
IEEE Trans. Image Processing 2006

Extraction of special effects caption text events from digital video
David Crandall, Sameer Antani, Rangachar Kasturi
IJDAR 2002
Robust Extraction of Text in Video
Sameer Antani, David Crandall, Rangachar Kasturi
ICPR 2000

Privacy and security

Deep Neural Network-based Detection and Verification of Microelectronic Images
Md Alimoor Reza, Zhenhua Chen, David Crandall
Journal of Hardware and Systems Security 2020
Automatically Detecting Bystanders in Photos to Reduce Privacy Risks
Rakibul Hasan, David Crandall, Mario Fritz, Apu Kapadia
OAKLAND 2020
Addressing supply chain risks of microelectronic devices through computer vision
Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David Crandall, Robert Templeman
AIPR 2017
Cartooning for enhanced privacy in lifelogging and streaming video
Eman Hassan, Rakibul Hasan, Patrick Shaffer, David Crandall, Apu Kapadia
CVPR CV-COPS 2017 2017
Enhancing Lifelogging Privacy by Detecting Screens
Mohammed Korayem, Robert Templeman, Dennis Chen, David Crandall, Apu Kapadia
CHI 2016
Honorable Mention Award!
PlaceAvoider: Steering First-Person Cameras away from Sensitive Spaces
Robert Templeman, Mohammed Korayem, David Crandall, Apu Kapadia
NDSS 2014
Reactive Security: Responding to Visual Stimuli from Wearable Cameras
Robert Templeman, Roberto Hoyle, David Crandall, Apu Kapadia
Ubicomp UPSIDE Workshop 2014
PlaceRaider: Virtual Theft in Physical Spaces with Smartphones
Robert Templeman, Zahidur Rahman, David Crandall, Apu Kapadia
NDSS 2013

Human visual learning

Learning the generative principles of a symbol system from limited examples
Lei Yuan, Violet Xiang, David Crandall, Linda Smith
Cognition 2020
A Computational Model of Early Word Learning from the Infant's Point of View
Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, Chen Yu
COGSCI 2020
How do infants start learning object names in a sea of clutter?
Hadar Karmazyn Raz, Drew Abney, David Crandall, Chen Yu, Linda Smith
COGSCI 2019
An Egocentric Perspective on Active Vision and Visual Object Learning in Toddlers
Sven Bambach, David Crandall, Linda Smith, Chen Yu
ICDL 2017
Exploring inter-observer differences in first-person object views using deep learning models
Sven Bambach, Zehua Zhang, David Crandall, Chen Yu
ICCV MBCC 2017 2017
Objects in the Center: How the Infant's Body Constrains Infant Scenes
Sven Bambach, Linda Smith, David Crandall, Chen Yu
ICDL 2016
Best paper award!
Active Viewing in Toddlers Facilitates Visual Object Learning: An Egocentric Vision Approach
Sven Bambach, David Crandall, Linda Smith, Chen Yu
COGSCI 2016
Understanding Embodied Visual Attention in Child-Parent Interaction
Sven Bambach, David Crandall, Chen Yu
ICDL 2013

Wearable camera attitudes and opportunities

Privacy Norms and Preferences for Photos Posted Online
Roberto Hoyle, Luke Stark, Qatrunnada Ismail, David Crandall, Apu Kapadia, Denise Anthony
TOCHI 2020
Can Privacy Be Satisfying? On Improving Viewer Satisfaction for Privacy-Enhanced Photos Using Aesthetic Transforms
Rakibul Hasan, Yifang Li, Eman Hassan, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia
CHI 2019
Viewer Experience of Obscuring Scene Elements in Photos to Enhance Privacy
Rakibul Hasan, Eman Hassan, Yifang Li, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia
CHI 2018
Addressing Physical Safety, Security, and Privacy for People with Visual Impairments
Tousif Ahmed, Patrick Shaffer, Kay Connelly, David Crandall, Apu Kapadia
SOUPS 2016
Sensitive Lifelogs: A Privacy Analysis of Photos from Wearable Cameras
Roberto Hoyle, Robert Templeman, Denise Anthony, David Crandall, Apu Kapadia
CHI 2015
Privacy Concerns and Behaviors of People with Visual Impairments
Tousif Ahmed, Roberto Hoyle, Kay Connelly, David Crandall, Apu Kapadia
CHI 2015
Privacy Behaviors of Lifeloggers using Wearable Cameras
Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, Apu Kapadia
UBICOMP 2014

Machine learning

Diverse Beam Search for Improved Description of Complex Scenes
Ashwin Vijayakumar, Michael Cogswell, Ramprasaath Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra
AAAI 2018
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David Crandall, Dhruv Batra
NeurIPS 2016
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
Ashwin K Vijayakumar, Michael Cogswell, Ramprasath Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra
2016

Computer vision for glaciology[More details on these projects]

Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S
Victor Berger, Mingze Xu, Mohanad Al-Ibadi, Shane Chu, David Crandall, John Paden, Geoffrey Fox
JSTARS 2019
Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction
Mingze Xu, Chenyou Fan, John Paden, Geoffrey Fox, David Crandall
WACV 2018
Automatic estimation of ice bottom surfaces from radar imagery
Mingze Xu, David Crandall, Geoffrey Fox, John Paden
ICIP 2017
Automatic Near Surface Estimation from Snow Radar Imagery
Jerome Mitchell, David Crandall, Geoffrey Fox, John Paden
IGARSS 2013
Layer-finding in radar echograms using probabilistic graphical models
David Crandall, Geoffrey Fox, John Paden
ICPR 2012

Modeling social networks

De-anonymizing users across heterogeneous social computing platforms
Mohammed Korayem, David Crandall
ICWSM 2013
Chelsea Won, and You Bought a T-shirt: Characterizing the Interplay Between Twitter and E-Commerce
Haipeng Zhang, Nish Parikh, Gyanit Singh, Neel Sundaresan
ASONAM 2013
Best paper award!
Inferring Social Ties from Geographic Coincidences
David Crandall, Lars Backstrom, Daniel Cosley, Siddharth Suri, Daniel Huttenlocher, Jon Kleinberg
PNAS 2010
Feedback Effects between Similarity and Social Influence in Online Communities
David Crandall, Daniel Cosley, Daniel Huttenlocher, Jon Kleinberg, Sid Suri
KDD 2008

Other projects

Automatic Annotation for Semantic Segmentation in Indoor Scenes
Md Alimoor Reza, Akshay Naik, Kai Chen, David Crandall
IROS 2019
Observing Pianist Accuracy and Form with Computer Vision
Jangwon Lee, Bardia Doosti, Yupeng Gu, David Cartledge, David Crandall, Christopher Raphael
WACV 2019
Hello Research! Developing an Intensive Research Experience for Undergraduate Women
Suzanne Menzel, Katie Siek, David Crandall
SIGCSE 2019
Towards Detecting Dyslexia in Children's Handwriting Using Neural Networks
Katie Spoon, David Crandall, Katie Siek
ICML Workshop on AI for Social Good 2019
Minimizing Supervision for Free-space Segmentation
Satoshi Tsutsui, Tommi Kerola, Shunta Saito, David Crandall
CVPR Workshop on Autonomous Driving 2018
From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review
Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Borner
EMBO Reports 2014
mFingerprint: Privacy-preserving user modeling with multimodal mobile device footprints
Haipeng Zhang, Zhixian Yan, Jun Yang, Emmanuel Munguia Tapia, David Crandall
SBP 2014
Solving Avatar Captchas automatically
Mohammed Korayem, Abdallah Mohamed, David Crandall, Roman Yampolskiy
AMLTA 2012
Subjectivity and Sentiment Analysis of Arabic: A Survey
Mohammed Korayem, David Crandall, Muhammad Abdul-Mageed
AMLTA 2012

The IU Computer Vision Lab's projects and activities have been funded, in part, by grants and contracts from the Air Force Office of Scientific Research (AFOSR), the Defense Threat Reduction Agency (DTRA), Dzyne Technologies, EgoVid, Inc., ETRI, Facebook, Google, Grant Thornton LLP, IARPA, the Indiana Innovation Institute (IN3), the IU Data to Insight Center, the IU Office of the Vice Provost for Research through an Emerging Areas of Research grant, the IU Social Sciences Research Commons, the Lilly Endowment, NASA, National Science Foundation (IIS-1253549, CNS-1834899, CNS-1408730, BCS-1842817, CNS-1744748, IIS-1257141, IIS-1852294), NVidia, ObjectVideo, Office of Naval Research (ONR), Pixm, Inc., and the U.S. Navy. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government, or any sponsor.