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GAS-GCN: Gated Action-Specific Graph Convolutional Networks for Skeleton-Based Action Recognition
Skeleton-based action recognition has achieved great advances with the development of graph convolutional networks (GCNs). Many existing GCNs-based models only use the fixed hand-crafted adjacency matrix to describe the connections between human body joints. This omits the important implicit connect...
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| Pubblicato in: | Sensors (Basel) |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7349730/ https://ncbi.nlm.nih.gov/pubmed/32575802 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20123499 |
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