no code implementations • 25 Apr 2024 • Yu Wang, Sanping Zhou, Kun Xia, Le Wang
Semi-supervised action recognition aims to improve spatio-temporal reasoning ability with a few labeled data in conjunction with a large amount of unlabeled data.
no code implementations • 17 Mar 2024 • Kun Xia, Le Wang, Sanping Zhou, Gang Hua, Wei Tang
To this end, we first devise innovative strategies to adaptively select high-quality positive and negative classes from the label space, by modeling both the confidence and rank of a class in relation to those of the target class.
1 code implementation • ICCV 2023 • Kun Xia, Le Wang, Sanping Zhou, Gang Hua, Wei Tang
To this end, we propose a unified framework, termed Noisy Pseudo-Label Learning, to handle both location biases and category errors.
no code implementations • CVPR 2022 • Kun Xia, Le Wang, Sanping Zhou, Nanning Zheng, Wei Tang
The main challenge of Temporal Action Localization is to retrieve subtle human actions from various co-occurring ingredients, e. g., context and background, in an untrimmed video.