方法证据记录
Spatial-Temporal GCN
Spatial-Temporal Graph Convolutional Networks (ST-GCN) is an architecture introduced by Yan et al. in 2018 for skeleton-based action recognition. By modeling human skeletons as graphs where joints are nodes and bones are edges, ST-GCN applies graph convolutions across space and time to recognize actions from skeleton sequences.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Spatial-Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
分类方法记录 · ml-model / deep-learning
打开完整方法 精选声明
声明已持久化到证据分类账中，每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时，此视图不会自行创建声明评估。
相关方法
从方法图中生成，显示为机器建议的关系 — 不推断任何证据声明。