| Convolutional two-stream network fusion for video action recognition C Feichtenhofer, A Pinz, AP Zisserman Computer Vision and Pattern Recognition (CVPR), 2016, 2016 | 3145 | 2016 |
| SlowFast Networks for Video Recognition C Feichtenhofer, H Fan, J Malik, K He International Conference on Computer Vision (ICCV), 2019, 2019 | 2778 | 2019 |
| A convnet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 2680 | 2022 |
| Multiscale Vision Transformers H Fan, B Xiong, K Mangalam, Y Li, Z Yan, J Malik, C Feichtenhofer International Conference on Computer Vision (ICCV), 2021, 2021 | 1905 | 2021 |
| Spatiotemporal Residual Networks for Video Action Recognition C Feichtenhofer, A Pinz, RP Wildes Advances in Neural Information Processing Systems, 3468-3476, 2016 | 1116* | 2016 |
| 3d human pose estimation in video with temporal convolutions and semi-supervised training D Pavllo, C Feichtenhofer, D Grangier, M Auli Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 959 | 2019 |
| X3D: Expanding architectures for efficient video recognition C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 798 | 2020 |
| Detect to track and track to detect C Feichtenhofer, A Pinz, A Zisserman Proceedings of the IEEE international conference on computer vision, 3038-3046, 2017 | 628 | 2017 |
| Trackformer: Multi-object tracking with transformers T Meinhardt, A Kirillov, L Leal-Taixe, C Feichtenhofer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 508 | 2022 |
| Long-term feature banks for detailed video understanding CY Wu, C Feichtenhofer, H Fan, K He, P Krahenbuhl, R Girshick Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 493 | 2019 |
| Masked feature prediction for self-supervised visual pre-training C Wei, H Fan, S Xie, CY Wu, A Yuille, C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 400 | 2022 |
| 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 | 357 | 2022 |
| MViTv2: Improved Multiscale Vision Transformers for Classification and Detection Y Li, CY Wu, H Fan, K Mangalam, B Xiong, J Malik, C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 353 | 2021 |
| VideoCLIP: Contrastive pre-training for zero-shot video-text understanding H Xu, G Ghosh, PY Huang, D Okhonko, A Aghajanyan, F Metze, ... Empirical Methods in Natural Language Processing (EMNLP) 2021, 2021 | 289 | 2021 |
| Masked autoencoders as spatiotemporal learners C Feichtenhofer, Y Li, K He Advances in neural information processing systems 35, 35946-35958, 2022 | 237 | 2022 |
| A large-scale study on unsupervised spatiotemporal representation learning C Feichtenhofer, H Fan, B Xiong, R Girshick, K He Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 198 | 2021 |
| Audiovisual slowfast networks for video recognition F Xiao, YJ Lee, K Grauman, J Malik, C Feichtenhofer arXiv preprint arXiv:2001.08740, 2020 | 192 | 2020 |
| Modeling human motion with quaternion-based neural networks D Pavllo, C Feichtenhofer, M Auli, D Grangier International Journal of Computer Vision 128, 855-872, 2020 | 164 | 2020 |
| Keeping your eye on the ball: Trajectory attention in video transformers M Patrick, D Campbell, Y Asano, I Misra, F Metze, C Feichtenhofer, ... Advances in neural information processing systems 34, 12493-12506, 2021 | 161 | 2021 |
| A perceptual image sharpness metric based on local edge gradient analysis C Feichtenhofer, H Fassold, P Schallauer IEEE Signal Processing Letters 20 (4), 379-382, 2013 | 131 | 2013 |
Jitendra MALIKProfessor of EECS, UC BerkeleyVerified email at eecs.berkeley.edu
