| Generating videos with scene dynamics C Vondrick, H Pirsiavash, A Torralba Advances In Neural Information Processing Systems (NIPS), 613-621, 2016 | 993 | 2016 |
| Globally-optimal greedy algorithms for tracking a variable number of objects H Pirsiavash, D Ramanan, CC Fowlkes CVPR 2011, 1201-1208, 2011 | 869 | 2011 |
| Detecting activities of daily living in first-person camera views H Pirsiavash, D Ramanan 2012 IEEE conference on computer vision and pattern recognition, 2847-2854, 2012 | 722 | 2012 |
| A large-scale benchmark dataset for event recognition in surveillance video S Oh, A Hoogs, A Perera, N Cuntoor, CC Chen, JT Lee, S Mukherjee, ... CVPR 2011, 3153-3160, 2011 | 633 | 2011 |
| Anticipating Visual Representations from Unlabeled Video AT Carl Vondrick, Hamed Pirsiavash Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on, 2016 | 392* | 2016 |
| Parsing IKEA Objects: Fine Pose Estimation JJ Lim, H Pirsiavash, A Torralba IEEE International Conference on Computer Vision (ICCV), 2013, 2013 | 245 | 2013 |
| Representation Learning by Learning to Count M Noroozi, H Pirsiavash, P Favaro International Conference on Computer Vision (ICCV), 2017, 2017 | 201 | 2017 |
| Weakly Supervised Cascaded Convolutional Networks A Diba, V Sharma, A Pazandeh, H Pirsiavash, L Van Gool Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, 2017 | 197 | 2017 |
| Bilinear classifiers for visual recognition H Pirsiavash, D Ramanan, CC Fowlkes Advances in neural information processing systems (NIPS), 1482-1490, 2009 | 161 | 2009 |
| Parsing videos of actions with segmental grammars H Pirsiavash, D Ramanan Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2014 | 158 | 2014 |
| Boosting Self-Supervised Learning via Knowledge Transfer M Noroozi, A Vinjimoor, P Favaro, H Pirsiavash International Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 144 | 2018 |
| Learning Aligned Cross-Modal Representations from Weakly Aligned Data AT Lluıs Castrejón, Yusuf Aytar, Carl Vondrick, Hamed Pirsiavash Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on, 2016 | 123* | 2016 |
| Assessing the quality of actions H Pirsiavash, C Vondrick, A Torralba European Conference on Computer Vision (ECCV), 556-571, 2014 | 117 | 2014 |
| Joint semantic segmentation and depth estimation with deep convolutional networks A Mousavian, H Pirsiavash, J Košecká 2016 Fourth International Conference on 3D Vision (3DV), 611-619, 2016 | 90 | 2016 |
| Talkminer: a lecture webcast search engine J Adcock, M Cooper, L Denoue, H Pirsiavash, LA Rowe Proceedings of the 18th ACM international conference on Multimedia, 241-250, 2010 | 88 | 2010 |
| Cross-Modal Scene Networks Y Aytar, L Castrejon, C Vondrick, H Pirsiavash, A Torralba IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017 | 78 | 2017 |
| Opti-acoustic stereo imaging: On system calibration and 3-D target reconstruction S Negahdaripour, H Sekkati, H Pirsiavash IEEE Transactions on image processing 18 (6), 1203-1214, 2009 | 76 | 2009 |
| Steerable part models H Pirsiavash, D Ramanan 2012 IEEE Conference on Computer Vision and Pattern Recognition, 3226-3233, 2012 | 75 | 2012 |
| Predicting Motivations of Actions by Leveraging Text C Vondrick, D Oktay, H Pirsiavash, A Torralba Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on …, 2016 | 50* | 2016 |
| Are all training examples equally valuable? A Lapedriza, H Pirsiavash, Z Bylinskii, A Torralba arXiv preprint arXiv:1311.6510, 2013 | 45 | 2013 |
Antonio TorralbaProfessor of Computer Science, MITVerified email at csail.mit.edu
