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Christoph Feichtenhofer
Christoph Feichtenhofer
Research Scientist, Facebook AI Research (FAIR)
Verified email at fb.com - Homepage
Title
Cited by
Cited by
Year
Convolutional two-stream network fusion for video action recognition
C Feichtenhofer, A Pinz, AP Zisserman
Computer Vision and Pattern Recognition (CVPR), 2016, 2016
25072016
SlowFast Networks for Video Recognition
C Feichtenhofer, H Fan, J Malik, K He
International Conference on Computer Vision (ICCV), 2019, 2019
13202019
Spatiotemporal Residual Networks for Video Action Recognition
C Feichtenhofer, A Pinz, RP Wildes
Advances in Neural Information Processing Systems, 3468-3476, 2016
914*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
5192019
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
4632017
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
3222019
X3D: Expanding architectures for efficient video recognition
C Feichtenhofer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
3182020
Multiscale Vision Transformers
H Fan, B Xiong, K Mangalam, Y Li, Z Yan, J Malik, C Feichtenhofer
arXiv preprint arXiv:2104.11227, 2021
1842021
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
1152022
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
1132022
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
1032020
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
1002013
Audiovisual slowfast networks for video recognition
F Xiao, YJ Lee, K Grauman, J Malik, C Feichtenhofer
arXiv preprint arXiv:2001.08740, 2020
902020
Temporal Residual Networks for Dynamic Scene Recognition
C Feichtenhofer, A Pinz, RP Wildes
Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, 2017
792017
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
702014
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
672020
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
662021
Grounded human-object interaction hotspots from video
T Nagarajan, C Feichtenhofer, K Grauman
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
582019
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
512022
What have we learned from deep representations for action recognition?
C Feichtenhofer, A Pinz, RP Wildes, A Zisserman
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
502018
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