Online Micro-gesture Recognition Using Data Augmentation and Spatial-Temporal Attention Article Swipe

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Pengyu Liu , Kun Li , Fei Wang , Yanyan Wei , Junhui She , Dan Guo ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2507.09512

In this paper, we introduce the latest solution developed by our team, HFUT-VUT, for the Micro-gesture Online Recognition track of the IJCAI 2025 MiGA Challenge. The Micro-gesture Online Recognition task is a highly challenging problem that aims to locate the temporal positions and recognize the categories of multiple micro-gesture instances in untrimmed videos. Compared to traditional temporal action detection, this task places greater emphasis on distinguishing between micro-gesture categories and precisely identifying the start and end times of each instance. Moreover, micro-gestures are typically spontaneous human actions, with greater differences than those found in other human actions. To address these challenges, we propose hand-crafted data augmentation and spatial-temporal attention to enhance the model's ability to classify and localize micro-gestures more accurately. Our solution achieved an F1 score of 38.03, outperforming the previous state-of-the-art by 37.9%. As a result, our method ranked first in the Micro-gesture Online Recognition track.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2507.09512
PDF: https://arxiv.org/pdf/2507.09512
OA Status: green
OpenAlex ID: https://openalex.org/W4414696231

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OpenAlex ID: https://openalex.org/W4414696231

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DOI: https://doi.org/10.48550/arxiv.2507.09512

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Title: Online Micro-gesture Recognition Using Data Augmentation and Spatial-Temporal Attention

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-07-13

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Authors: Pengyu Liu, Kun Li, Fei Wang, Yanyan Wei, Junhui She, Dan Guo

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Landing page: https://arxiv.org/abs/2507.09512

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PDF URL: https://arxiv.org/pdf/2507.09512

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Open access: Yes

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OA status: green

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OA URL: https://arxiv.org/pdf/2507.09512

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Cited by: 0

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