| Convolutional two-stream network fusion for video action recognition C Feichtenhofer, A Pinz, AP Zisserman Computer Vision and Pattern Recognition (CVPR), 2016, 2016 | 2573 | 2016 |
| SlowFast Networks for Video Recognition C Feichtenhofer, H Fan, J Malik, K He International Conference on Computer Vision (ICCV), 2019, 2019 | 1454 | 2019 |
| Spatiotemporal Residual Networks for Video Action Recognition C Feichtenhofer, A Pinz, RP Wildes Advances in Neural Information Processing Systems, 3468-3476, 2016 | 931* | 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 | 558 | 2019 |
| 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 | 483 | 2017 |
| X3D: Expanding architectures for efficient video recognition C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 365 | 2020 |
| 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 | 336 | 2019 |
| Multiscale Vision Transformers H Fan, B Xiong, K Mangalam, Y Li, Z Yan, J Malik, C Feichtenhofer arXiv preprint arXiv:2104.11227, 2021 | 248 | 2021 |
| 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 | 224 | 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 | 149 | 2022 |
| Modeling human motion with quaternion-based neural networks D Pavllo, C Feichtenhofer, M Auli, D Grangier International Journal of Computer Vision 128 (4), 855-872, 2020 | 108 | 2020 |
| 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 | 103 | 2013 |
| Audiovisual slowfast networks for video recognition F Xiao, YJ Lee, K Grauman, J Malik, C Feichtenhofer arXiv preprint arXiv:2001.08740, 2020 | 101 | 2020 |
| 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 | 86 | 2021 |
| Temporal Residual Networks for Dynamic Scene Recognition C Feichtenhofer, A Pinz, RP Wildes Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, 2017 | 80 | 2017 |
| A multigrid method for efficiently training video models CY Wu, R Girshick, K He, C Feichtenhofer, P Krahenbuhl Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 74 | 2020 |
| 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 | 71 | 2022 |
| Bags of Spacetime Energies for Dynamic Scene Recognition C Feichtenhofer, A Pinz, RP Wildes Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014 | 71 | 2014 |
| Grounded human-object interaction hotspots from video T Nagarajan, C Feichtenhofer, K Grauman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 60 | 2019 |
| 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 | 52 | 2021 |
Axel PinzAssociate Professor, Graz University of TechnologyVerified email at tugraz.at
