Spatial–Temporal Heatmap Masked Autoencoder for Skeleton-Based Action Recognition

Skeleton representation learning offers substantial advantages for action recognition by encoding intricate motion details and spatial–temporal dependencies among joints. However, fully supervised approaches necessitate large amounts of annotated data, which are often labor-intensive and costly to a...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 25; číslo 10; s. 3146
Hlavní autoři:	Bian, Cunling, Yang, Yang, Wang, Tao, Lu, Weigang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 16.05.2025 MDPI
Témata:	Artificial intelligence Comparative analysis Computer vision Human acts Human behavior Identification and classification Machine learning Machine vision masked autoencoder Methods Neural networks self-supervised learning Semantics skeleton-based action recognition spatial–temporal heatmap visual transformer China masked autoencoder self-supervised learning skeleton-based action recognition spatial–temporal heatmap visual transformer
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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