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Christoph Feichtenhofer
Christoph Feichtenhofer
Meta, FAIR
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Titel
Zitiert von
Zitiert von
Jahr
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
70282022
SlowFast Networks for Video Recognition
C Feichtenhofer, H Fan, J Malik, K He
International Conference on Computer Vision (ICCV), 2019, 2019
42092019
Convolutional two-stream network fusion for video action recognition
C Feichtenhofer, A Pinz, AP Zisserman
Computer Vision and Pattern Recognition (CVPR), 2016, 2016
36082016
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
24932024
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
15702021
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
13952019
X3D: Expanding architectures for efficient video recognition
C Feichtenhofer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
12802020
Spatiotemporal Residual Networks for Video Action Recognition
C Feichtenhofer, A Pinz, RP Wildes
Advances in Neural Information Processing Systems, 3468-3476, 2016
1259*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
9932022
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
9422022
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
8612021
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
7422022
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
7332017
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
6042019
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
5862021
Masked autoencoders as spatiotemporal learners
C Feichtenhofer, Y Li, K He
Advances in neural information processing systems 35, 35946-35958, 2022
5652022
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
4192024
Token merging: Your vit but faster
D Bolya, CY Fu, X Dai, P Zhang, C Feichtenhofer, J Hoffman
arXiv preprint arXiv:2210.09461, 2022
3882022
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
3162023
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
3122021
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