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ASQuery: A Query-based Model for Action Segmentation

2024-09-302024 IEEE International Conference on Multimedia and Expo (ICME) 2024Code Available1· sign in to hype

Gan Ziliang, Jin Lei, Nie Lei, Zheng Wang, Li Zhou, Li Liang, Wang Zhecan, Li Jianshu, Xing Junliang, Zhao Jian

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Abstract

For the task of temporal action segmentation, existing works commonly treat it as a frame-wise classification problem. In this paper, we propose a straight but effective model namely ASQuery by learning central representation of each action category, which transforms the classification problem to the similarity calculation between category-specific queries and frame features. These central representations are dynamically generated through our Transformer decoder module, endowing them more flexible and comprehensive perception of the whole video. Moreover, we first introduce the boundary query for refining segmentation results, aiding to alleviating the troublesome over-segmentation problem. ASQuery demonstrates superior performance compared to state-of-the-art models, achieving improvements of 0.9% and 4.1% in the mean metrics on two public action segmentation datasets, i.e., Breakfast and Assembly101, respectively. The source codes are available at https://github.com/zlngan/ASQuery.

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