Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition

Graph Convolutional Networks (GCNs) have attracted a lot of attention and shown remarkable performance for action recognition in recent years. For improving the recognition accuracy, how to build graph structure adaptively, select key frames and extract discriminative features are the key problems o...

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Detalles Bibliográficos
Autores principales: Liu, Di, Xu, Hui, Wang, Jianzhong, Lu, Yinghua, Kong, Jun, Qi, Miao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538327/
https://www.ncbi.nlm.nih.gov/pubmed/34695972
http://dx.doi.org/10.3390/s21206761

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538327/
https://www.ncbi.nlm.nih.gov/pubmed/34695972
http://dx.doi.org/10.3390/s21206761

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