Spatial‐temporal slowfast graph convolutional network for skeleton‐based action recognition
Abstract In skeleton‐based action recognition, the graph convolutional network (GCN) has achieved great success. Modelling skeleton data in a suitable spatial‐temporal way and designing the adjacency matrix are crucial aspects for GCN‐based methods to capture joint relationships. In this study, we p...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cvi2.12080 |