Cross-Model Pseudo-Labeling for Semi-Supervised Action Recognition-Reference-Cited by-同舟云学术

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Cross-Model Pseudo-Labeling for Semi-Supervised Action Recognition

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Xu Yinghao¹,Wei Fangyun²,Sun Xiao²,Yang Ceyuan¹,Shen Yujun¹,Dai Bo³,Zhou Bolei¹,Lin Stephen²

Affiliation:

1. The Chinese University of Hong Kong

2. Microsoft Research Asia

3. S-Lab, Nanyang Technological University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09879333.pdf?arnumber=9879333

Reference34 articles.

1. Trajectory convolution for action recognition;zhao;Adv Neural Inform Process Syst,2018

2. S41: Self-supervised semi-supervised learning;zhai;Proceedings of the IEEE/CVF International Conference on Computer Vision,0

3. Semi-supervised convolutional neural networks for human activity recognition;ming;IEEE International Conference on Big Data IEEE,0

4. Temporal Pyramid Network for Action Recognition

5. Temporal relational reasoning in videos;zhou;Eur Conf Comput Vis,0

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3. Integrating pseudo labeling with contrastive clustering for transformer-based semi-supervised action recognition;Applied Intelligence;2024-08-10

4. How to Improve Video Analytics with Action Recognition: A Survey;ACM Computing Surveys;2024-08-08

5. TNCB: Tri-Net With Cross-Balanced Pseudo Supervision for Class Imbalanced Medical Image Classification;IEEE Journal of Biomedical and Health Informatics;2024-04

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