T[sub.ohjm]-Trained Multiscale Spatial Temporal Graph Convolutional Neural Network for Semi-Supervised Skeletal Action Recognition
In recent years, spatial-temporal graph convolutional networks have played an increasingly important role in skeleton-based human action recognition. However, there are still three major limitations to most ST-GCN-based approaches: (1) They only use a single joint scale to extract action features, o...
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Veröffentlicht in: | Electronics (Basel) 2022, Vol.11 (21) |
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Format: | Report |
Sprache: | eng |
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