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Cross-Domain Semantic-Enhanced Adaptive Graph Fusion Network for Robust Skeleton Action Recognition

2025-12-30

Abstract excerpt

Human action recognition (HAR) remains challenging, particularly for skeleton-based methods due to issues like domain shift and limited deep semantic understanding. Traditional Graph Convolutional Networks often struggle with effective cross-domain adaptation and inferring complex semantic relationships. To address these limitations, we propose CD-SEAFNet, a novel framework meticulously designed to significantly e...

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Literature Corpus work
b6c266e8-ae82-5c19-8448-a7aae655436e
DOI
10.20944/preprints202512.2690.v1
Open publication

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Cross-Domain Semantic-Enhanced Adaptive Graph Fusion Network for Robust Skeleton Action RecognitionDOI 10.20944/preprints202512.2690.v1
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