| 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 | 6922 | 2022 |
| SlowFast Networks for Video Recognition C Feichtenhofer, H Fan, J Malik, K He International Conference on Computer Vision (ICCV), 2019, 2019 | 4175 | 2019 |
| Convolutional two-stream network fusion for video action recognition C Feichtenhofer, A Pinz, AP Zisserman Computer Vision and Pattern Recognition (CVPR), 2016, 2016 | 3595 | 2016 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 2246 | 2024 |
| 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 | 1545 | 2021 |
| 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 | 1390 | 2019 |
| X3D: Expanding architectures for efficient video recognition C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 1268 | 2020 |
| Spatiotemporal Residual Networks for Video Action Recognition C Feichtenhofer, A Pinz, RP Wildes Advances in Neural Information Processing Systems, 3468-3476, 2016 | 1253* | 2016 |
| 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 | 986 | 2022 |
| 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 | 931 | 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 | 851 | 2021 |
| 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 | 735 | 2022 |
| 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 | 731 | 2017 |
| 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 | 602 | 2019 |
| 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 | 582 | 2021 |
| Masked autoencoders as spatiotemporal learners C Feichtenhofer, Y Li, K He Advances in neural information processing systems 35, 35946-35958, 2022 | 556 | 2022 |
| SAM 2: Segment anything in images and videos N Ravi, V Gabeur, YT Hu, R Hu, C Ryali, T Ma, H Khedr, R Rädle, ... arXiv preprint arXiv:2408.00714, 2024 | 392 | 2024 |
| Token merging: Your vit but faster D Bolya, CY Fu, X Dai, P Zhang, C Feichtenhofer, J Hoffman arXiv preprint arXiv:2210.09461, 2022 | 381 | 2022 |
| Scaling language-image pre-training via masking Y Li, H Fan, R Hu, C Feichtenhofer, K He Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 315 | 2023 |
| 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 | 307 | 2021 |
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