CVJul 5, 2024

Micro-gesture Online Recognition using Learnable Query Points

arXiv:2407.04490v118 citationsh-index: 17
AI Analysis

This work addresses the specific challenge of micro-gesture recognition in videos, which is incremental as it builds on existing temporal action detection methods.

The paper tackled the problem of identifying and locating micro-gestures in video clips for online recognition, achieving a second-place ranking in the MiGA challenge at IJCAI 2024.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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