English

Micro-gesture Online Recognition using Learnable Query Points

Computer Vision and Pattern Recognition 2024-07-08 v1

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.

Cite

@article{arxiv.2407.04490,
  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},
  journal= {arXiv preprint arXiv:2407.04490},
  year   = {2024}
}

Comments

Technical Report of HFUT-VUT for the MiGA challenge at IJCAI 2024

R2 v1 2026-06-28T17:30:14.527Z