Mapping the world's photos DJ Crandall, L Backstrom, D Huttenlocher, J Kleinberg Proceedings of the 18th international conference on World wide web, 761-770, 2009 | 1109 | 2009 |
Feedback effects between similarity and social influence in online communities D Crandall, D Cosley, D Huttenlocher, J Kleinberg, S Suri Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 876 | 2008 |
Ego4d: Around the world in 3,000 hours of egocentric video K Grauman, A Westbury, E Byrne, Z Chavis, A Furnari, R Girdhar, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 705 | 2022 |
Inferring social ties from geographic coincidences DJ Crandall, L Backstrom, D Cosley, S Suri, D Huttenlocher, J Kleinberg Proceedings of the National Academy of Sciences 107 (52), 22436-22441, 2010 | 615 | 2010 |
Diverse beam search: Decoding diverse solutions from neural sequence models AK Vijayakumar, M Cogswell, RR Selvaraju, Q Sun, S Lee, D Crandall, ... arXiv preprint arXiv:1610.02424, 2016 | 536 | 2016 |
Lending a hand: Detecting hands and recognizing activities in complex egocentric interactions S Bambach, S Lee, DJ Crandall, C Yu Proceedings of the IEEE international conference on computer vision, 1949-1957, 2015 | 503 | 2015 |
Discrete-continuous optimization for large-scale structure from motion D Crandall, A Owens, N Snavely, D Huttenlocher CVPR 2011, 3001-3008, 2011 | 450 | 2011 |
Spatial priors for part-based recognition using statistical models. D Crandall, P Felzenszwalb, D Huttenlocher IEEE Conference on Computer Vision and Pattern Recognition, 2005 | 432 | 2005 |
Dynamic dual-attentive aggregation learning for visible-infrared person re-identification M Ye, J Shen, D J. Crandall, L Shao, J Luo Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 382 | 2020 |
Landmark classification in large-scale image collections Y Li, DJ Crandall, DP Huttenlocher 2009 IEEE 12th international conference on computer vision, 1957-1964, 2009 | 377 | 2009 |
Discovering Localized Attributes for Fine-grained Recognition K Duan, D Parikh, D Crandall, K Grauman CVPR, 2012 | 357 | 2012 |
Why m heads are better than one: Training a diverse ensemble of deep networks S Lee, S Purushwalkam, M Cogswell, D Crandall, D Batra arXiv preprint arXiv:1511.06314, 2015 | 320 | 2015 |
Zero-shot video object segmentation via attentive graph neural networks W Wang, X Lu, J Shen, DJ Crandall, L Shao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 312 | 2019 |
Weakly supervised learning of part-based spatial models for visual object recognition DJ Crandall, DP Huttenlocher Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz …, 2006 | 264 | 2006 |
Privacy behaviors of lifeloggers using wearable cameras R Hoyle, R Templeman, S Armes, D Anthony, D Crandall, A Kapadia Proceedings of the 2014 ACM international joint conference on pervasive and …, 2014 | 241 | 2014 |
Diverse beam search for improved description of complex scenes A Vijayakumar, M Cogswell, R Selvaraju, Q Sun, S Lee, D Crandall, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 239 | 2018 |
Hope-net: A graph-based model for hand-object pose estimation B Doosti, S Naha, M Mirbagheri, DJ Crandall Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 216 | 2020 |
Real-time, cloud-based object detection for unmanned aerial vehicles J Lee, J Wang, D Crandall, S Šabanović, G Fox 2017 First IEEE International Conference on Robotic Computing (IRC), 36-43, 2017 | 206 | 2017 |
A survey on deep learning technique for video segmentation T Zhou, F Porikli, DJ Crandall, L Van Gool, W Wang IEEE transactions on pattern analysis and machine intelligence 45 (6), 7099-7122, 2022 | 205* | 2022 |
Stochastic multiple choice learning for training diverse deep ensembles S Lee, S Purushwalkam Shiva Prakash, M Cogswell, V Ranjan, ... Advances in Neural Information Processing Systems 29, 2016 | 204 | 2016 |