Work

Micro-gesture Online Recognition using Learnable Query Points

Year: 2024

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2407.04490

Authors: Liu, Pengyu, Wang, Fei, Li, Kun, Chen, Guoliang, Wei, Yanyan, Tang, Shengeng, Wu, Zhiliang, Guo, Dan

Institutions: Hefei University of Technology, Zhejiang University

Language: English

Topic: Human Pose and Action Recognition

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities

Awards: G4862433228, G5038960961, G6151690139, G8480155402

OpenAlex ID: W4400434853

Cites: 7

Cited by: 30

Related to: 10