Multi-Stream and Enhanced Spatial-Temporal Graph Convolution Network for Skeleton-Based Action Recognition
In skeleton-based human action recognition, spatial-temporal graph convolution networks (ST-GCNs) have achieved remarkable performances recently. However, how to explore more discriminative spatial and temporal features is still an open problem. The temporal graph convolution of the traditional ST-G...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9098932/ |