Temporal‐enhanced graph convolution network for skeleton‐based action recognition
Abstract Graph convolution networks (GCNs) have drawn attention for skeleton‐based action recognition. They have achieved remarkable performance by adaptively learning spatial features of human action dynamics. However, the existing methods are limited in temporal sequence modelling of human actions...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Wiley
2022-04-01
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| coleção: | IET Computer Vision |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1049/cvi2.12086 |
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