Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition-Reference-Cited by-同舟云学术

Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition

Published:2020-10-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM International Conference on Multimedia
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Author:

Fu Yuqian¹,Zhang Li²,Wang Junke¹,Fu Yanwei¹,Jiang Yu-Gang¹

Affiliation:

1. Fudan University, Shanghai, China

2. University of Oxford, Oxford, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394171.3413502

Reference73 articles.

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2. Kaidi Cao Jingwei Ji Zhangjie Cao Chien-Yi Chang and Juan Carlos Niebles. 2020. Few-shot video classification via temporal alignment. In CVPR. Kaidi Cao Jingwei Ji Zhangjie Cao Chien-Yi Chang and Juan Carlos Niebles. 2020. Few-shot video classification via temporal alignment. In CVPR.

3. Joao Carreira and Andrew Zisserman. 2017. Quo vadis action recognition? a new model and the kinetics dataset. In CVPR. Joao Carreira and Andrew Zisserman. 2017. Quo vadis action recognition? a new model and the kinetics dataset. In CVPR.

4. Ya-Liang Chang Zhe Yu Liu Kuan-Ying Lee and Winston Hsu. 2019. Learnable gated temporal shift module for deep video inpainting. arXiv preprint (2019). Ya-Liang Chang Zhe Yu Liu Kuan-Ying Lee and Winston Hsu. 2019. Learnable gated temporal shift module for deep video inpainting. arXiv preprint (2019).

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