Micro-gesture Online Recognition using Learnable Query Points

Pengyu Liu, Fei Wang, Kun Li, Guoliang Chen, Yanyan Wei +3 more
7/5/2024
cs.CV

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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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Cite this paper

@article{liu2024microgesture,
  title  = {Micro-gesture Online Recognition using Learnable Query Points},
  author = {Pengyu Liu and Fei Wang and Kun Li and Guoliang Chen and Yanyan Wei and Shengeng Tang and Zhiliang Wu and Dan Guo},
  year   = {2024},
  eprint = {2407.04490},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.04490v1}
}

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