Part-Aware Unified Representation of Language and Skeleton for Zero-Shot Action Recognition

While remarkable progress has been made on supervised skeleton-based action recognition, the challenge of zero-shot recognition remains relatively unexplored. In this pa-per, we argue that relying solely on aligning label-level se-mantics and global skeleton features is insufficient to effectively t...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 18761 - 18770
Hlavní autori:	Zhu, Anqi, Ke, Qiuhong, Gong, Mingming, Bailey, James
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 16.06.2024
Predmet:	action recognition Computer vision contrastive learning large language model Large language models Natural languages Pattern recognition representation learning Skeleton skeleton action recognition Source coding Visualization zero-shot learning
ISSN:	1063-6919
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