| The kinetics human action video dataset W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ... arXiv preprint arXiv:1705.06950, 2017 | 4267 | 2017 |
| Beyond short snippets: Deep networks for video classification J Yue-Hei Ng, M Hausknecht, S Vijayanarasimhan, O Vinyals, R Monga, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 3019 | 2015 |
| Youtube-8m: A large-scale video classification benchmark S Abu-El-Haija, N Kothari, J Lee, P Natsev, G Toderici, B Varadarajan, ... arXiv preprint arXiv:1609.08675, 2016 | 1456 | 2016 |
| Ava: A video dataset of spatio-temporally localized atomic visual actions C Gu, C Sun, DA Ross, C Vondrick, C Pantofaru, Y Li, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1116 | 2018 |
| Rethinking the faster r-cnn architecture for temporal action localization YW Chao, S Vijayanarasimhan, B Seybold, DA Ross, J Deng, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 755 | 2018 |
| Sfm-net: Learning of structure and motion from video S Vijayanarasimhan, S Ricco, C Schmid, R Sukthankar, K Fragkiadaki arXiv preprint arXiv:1704.07804, 2017 | 504 | 2017 |
| Fast, accurate detection of 100,000 object classes on a single machine T Dean, MA Ruzon, M Segal, J Shlens, S Vijayanarasimhan, J Yagnik Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 434 | 2013 |
| Large-scale live active learning: Training object detectors with crawled data and crowds S Vijayanarasimhan, K Grauman International journal of computer vision 108, 97-114, 2014 | 416 | 2014 |
| What's it going to cost you?: Predicting effort vs. informativeness for multi-label image annotations S Vijayanarasimhan, K Grauman 2009 IEEE conference on computer vision and pattern recognition, 2262-2269, 2009 | 224 | 2009 |
| Keywords to visual categories: Multiple-instance learning forweakly supervised object categorization S Vijayanarasimhan, K Grauman 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 174 | 2008 |
| Active frame selection for label propagation in videos S Vijayanarasimhan, K Grauman Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 152 | 2012 |
| The kinetics human action video dataset. arXiv 2017 W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ... arXiv preprint arXiv:1705.06950, 2017 | 138 | 2017 |
| Hashing hyperplane queries to near points with applications to large-scale active learning P Jain, S Vijayanarasimhan, K Grauman Advances in Neural Information Processing Systems 23, 2010 | 129 | 2010 |
| Far-sighted active learning on a budget for image and video recognition S Vijayanarasimhan, P Jain, K Grauman 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 111 | 2010 |
| End-to-end learning of semantic grasping E Jang, S Vijayanarasimhan, P Pastor, J Ibarz, S Levine arXiv preprint arXiv:1707.01932, 2017 | 108 | 2017 |
| Actively selecting annotations among objects and attributes A Kovashka, S Vijayanarasimhan, K Grauman 2011 International Conference on Computer Vision, 1403-1410, 2011 | 101 | 2011 |
| Efficient region search for object detection S Vijayanarasimhan, K Grauman CVPR 2011, 1401-1408, 2011 | 99 | 2011 |
| Multi-level active prediction of useful image annotations for recognition S Vijayanarasimhan, K Grauman Advances in Neural Information Processing Systems 21, 2008 | 99 | 2008 |
| Weakly supervised learning of object segmentations from web-scale video G Hartmann, M Grundmann, J Hoffman, D Tsai, V Kwatra, O Madani, ... Computer Vision–ECCV 2012. Workshops and Demonstrations: Florence, Italy …, 2012 | 82 | 2012 |
| Deep networks with large output spaces S Vijayanarasimhan, J Shlens, R Monga, J Yagnik arXiv preprint arXiv:1412.7479, 2014 | 71 | 2014 |
