Enhanced Spatial and Extended Temporal Graph Convolutional Network for Skeleton-Based Action Recognition

In the skeleton-based human action recognition domain, the spatial-temporal graph convolution networks (ST-GCNs) have made great progress recently. However, they use only one fixed temporal convolution kernel, which is not enough to extract the temporal cues comprehensively. Moreover, simply connect...

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Detalles Bibliográficos
Autores principales: Li, Fanjia, Li, Juanjuan, Zhu, Aichun, Xu, Yonggang, Yin, Hongsheng, Hua, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571203/
https://www.ncbi.nlm.nih.gov/pubmed/32942579
http://dx.doi.org/10.3390/s20185260

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571203/
https://www.ncbi.nlm.nih.gov/pubmed/32942579
http://dx.doi.org/10.3390/s20185260

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