| Action Recognition by Dense Trajectories Heng Wang, Alexander Klaser, Cordelia Schmid, Cheng-Lin Liu Proceedings of the IEEE conference on Computer Vision and Pattern …, 2011 | 3780* | 2011 |
| Action recognition with improved trajectories H Wang, C Schmid Proceedings of the IEEE international conference on computer vision, 3551-3558, 2013 | 3685 | 2013 |
| A closer look at spatiotemporal convolutions for action recognition D Tran, H Wang, L Torresani, J Ray, Y LeCun, M Paluri Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 2326 | 2018 |
| Dense trajectories and motion boundary descriptors for action recognition H Wang, A Kläser, C Schmid, CL Liu International journal of computer vision 103, 60-79, 2013 | 1909 | 2013 |
| Evaluation of local spatio-temporal features for action recognition H Wang, MM Ullah, A Klaser, I Laptev, C Schmid Bmvc 2009-british machine vision conference, 124.1-124.11, 2009 | 1740 | 2009 |
| Is space-time attention all you need for video understanding? G Bertasius, H Wang, L Torresani ICML 2 (3), 4, 2021 | 765 | 2021 |
| Video Classification with Channel-Separated Convolutional Networks D Tran, H Wang, L Torresani, M Feiszli Proceedings of the IEEE International Conference on Computer Vision, 5552-5561, 2019 | 471 | 2019 |
| A robust and efficient video representation for action recognition H Wang, D Oneata, J Verbeek, C Schmid International journal of computer vision 119, 219-238, 2016 | 334 | 2016 |
| Large-scale weakly-supervised pre-training for video action recognition D Ghadiyaram, M Feiszli, D Tran, X Yan, H Wang, D Mahajan arXiv preprint arXiv:1905.00561, 2019 | 304 | 2019 |
| Lear-inria submission for the thumos workshop H Wang, C Schmid ICCV workshop on action recognition with a large number of classes 2 (7), 8, 2013 | 115 | 2013 |
| Video Modeling with Correlation Networks H Wang, D Tran, L Torresani, M Feiszli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 114 | 2020 |
| Leveraging the present to anticipate the future in videos A Miech, I Laptev, J Sivic, H Wang, L Torresani, D Tran Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 59 | 2019 |
| FASTER Recurrent Networks for Efficient Video Classification L Zhu, D Tran, L Sevilla-Lara, Y Yang, M Feiszli, H Wang The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 | 53 | 2020 |
| The AXES submissions at TrecVid 2013 R Aly, R Arandjelovic, K Chatfield, M Douze, B Fernando, Z Harchaoui, ... | 50* | 2013 |
| Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation W Wang, M Feiszli, H Wang, D Tran arXiv preprint arXiv:2104.04691, 2021 | 41 | 2021 |
| Axes at trecvid 2012: Kis, ins, and med D Oneata, M Douze, J Revaud, S Jochen, D Potapov, H Wang, ... TRECVID workshop, 2012 | 37* | 2012 |
| Devon: Deformable Volume Network for Learning Optical Flow Y Lu, J Valmadre, H Wang, J Kannala, M Harandi, PHS Torr IEEE Winter Conference on Applications of Computer Vision, 2020 | 34 | 2020 |
| Scenes-Objects-Actions: A Multi-Task, Multi-Label Video Dataset J Ray, H Wang, D Tran, Y Wang, M Feiszli, L Torresani, M Paluri The European Conference on Computer Vision (ECCV), 2018 | 32 | 2018 |
| SLAC: A sparsely labeled dataset for action classification and localization H Zhao, Z Yan, H Wang, L Torresani, A Torralba arXiv preprint arXiv:1712.09374 2, 2017 | 31 | 2017 |
| PyTorchVideo: A Deep Learning Library for Video Understanding Haoqi Fan, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Yanghao Li ... Proceedings of the 29th ACM International Conference on Multimedia, 2021 | 26 | 2021 |
Cordelia SchmidResearch director INRIA Verified email at inria.fr
