• 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, accepted, to appear) [ 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. [ 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. [ 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. [ 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. [ 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. [ 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. [ 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," 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]
  • 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. [ 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]























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.