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arXiv · 2407.04490

Micro-gesture Online Recognition using Learnable Query Points

Pengyu Liu·Fei Wang·Kun Li·Guoliang Chen·Yanyan Wei·Shengeng Tang·Zhiliang Wu·Dan Guo
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Abstract

In this paper, we briefly introduce the solution developed by our team, HFUT-VUT, for the Micro-gesture Online Recognition track in the MiGA challenge at IJCAI 2024. The Micro-gesture Online Recognition task involves identifying the category and locating the start and end times of micro-gestures in video clips. Compared to the typical Temporal Action Detection task, the Micro-gesture Online Recognition task focuses more on distinguishing between micro-gestures and pinpointing the start and end times of actions. Our solution ranks 2nd in the Micro-gesture Online Recognition track.

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Pengyu Liu, Fei Wang, Kun Li, Guoliang Chen, Yanyan Wei, Shengeng Tang, Zhiliang Wu, Dan Guo. 2024-07-05. Micro-gesture Online Recognition using Learnable Query Points. https://arxiv.org/abs/2407.04490

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