| Interact before align: Leveraging cross-modal knowledge for domain adaptive action recognition L Yang, Y Huang, Y Sugano, Y Sato Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 39 | 2022 |
| Compound prototype matching for few-shot action recognition Y Huang, L Yang, Y Sato European Conference on Computer Vision, 351-368, 2022 | 33 | 2022 |
| Weakly supervised temporal sentence grounding with uncertainty-guided self-training Y Huang, L Yang, Y Sato Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 19 | 2023 |
| Deco: Decomposition and reconstruction for compositional temporal grounding via coarse-to-fine contrastive ranking L Yang, Q Kong, HK Yang, W Kehl, Y Sato, N Kobori Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 7 | 2023 |
| Leveraging human selective attention for medical image analysis with limited training data Y Huang, X Li, L Yang, L Gu, Y Zhu, H Seo, Q Meng, T Harada, Y Sato arXiv preprint arXiv:2112.01034, 2021 | 7 | 2021 |
| Epic-kitchens-100 unsupervised domain adaptation challenge for action recognition 2021: Team m3em technical report L Yang, Y Huang, Y Sugano, Y Sato arXiv preprint arXiv:2106.10026, 2021 | 7 | 2021 |
| EgoExoLearn: A Dataset for Bridging Asynchronous Ego-and Exo-centric View of Procedural Activities in Real World Y Huang, G Chen, J Xu, M Zhang, L Yang, B Pei, H Zhang, L Dong, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 5 | 2024 |
| Stacked temporal attention: Improving first-person action recognition by emphasizing discriminative clips L Yang, Y Huang, Y Sugano, Y Sato arXiv preprint arXiv:2112.01038, 2021 | 5 | 2021 |
| Matching Compound Prototypes for Few-Shot Action Recognition Y Huang, L Yang, G Chen, H Zhang, F Lu, Y Sato International Journal of Computer Vision, 1-26, 2024 | 1 | 2024 |
Yoichi SatoProfessor, Institute of Industrial Science, The University of Tokyo在 iis.u-tokyo.ac.jp 的电子邮件经过验证
Yoichi SatoProfessor, Institute of Industrial Science, The University of Tokyo在 iis.u-tokyo.ac.jp 的电子邮件经过验证