讀書筆記：Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition
Dynamic GCN：基於骨架的動作識別的上下文豐富的拓撲學習 Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition code：暫時未公開 摘要： 圖卷積網絡（GCN）對基於骨骼的動作識別任務越來越感興趣。關鍵在於圖形結構的設計，該結構對骨架拓撲信息進行編碼。在本文中，我們提
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相關文章
- 1. 3DV（讀書筆記）3DV: 3D Dynamic Voxel for Action Recognition in Depth Video
- 2. 讀書筆記5：Deep Progressive Reinforcement Learning for Skeleton-based Action Recognition
- 3. 論文閱讀《Dynamic Image Networks for Action Recognition》
- 4. DDGCN: A Dynamic Directed Graph Convolutional Network for Action Recognition
- 5. 閱讀筆記Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by NS(AAAI2020)
- 6. Collaborative Spatiotemporal Feature Learning for Video Action Recognition 閱讀筆記
- 7. 《Collaborative Spatioitemporal Feature Learning for Video Action Recognition》閱讀
- 8. 讀書筆記9：Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
- 9. Two-Stream Convolutional Networks for Action Recognition in Videos讀書筆記
- 10. 讀書筆記1：Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition