Adaptive Channel-Enhanced Graph Convolution for Skeleton-Based Human Action Recognition
Obtaining discriminative joint features is crucial for skeleton-based human action recognition. Current models mainly focus on the research of skeleton topology encoding. However, their predefined topology is the same and fixed for all action samples, making it challenging to obtain discriminative j...
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| Asıl Yazarlar: | , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI AG
2024-09-01
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| Seri Bilgileri: | Applied Sciences |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/2076-3417/14/18/8185 |
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