An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
先把論文的框架放到這裏，我再聊一下我覺得比較有意思的地方（如果有不對的地方請多多指教） 1.LSTM裏用了圖卷積（畢竟是骨架結構） 公式如下 2.LSTM裏集成了注意力，而且這個最後輸出是最後一行的Ht，fatt是注意力模型 注意力模型 3.骨架通過FC用n*256維的空間表示 4.FA負責找前後兩幀的差異 5.LSTM層連接了FC與FA的內容（通過contact） 6.TAP：池化層，只不過是時
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- 1. An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 2. 【論文翻譯】An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 3. paper reading：Part-based Graph Convolutional Network for Action Recognition
- 4. DDGCN: A Dynamic Directed Graph Convolutional Network for Action Recognition
- 5. Self-Attention Network for Skeleton-based Human Action Recognition
- 6. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
- 7. 譯：Convolutional Two-Stream Network Fusion for Video Action Recognition
- 8. Part-based Graph Convolutional Network for Action Recognition論文筆記
- 9. [行爲識別]RPAN：An end-to-end recurrent pose-attention network for action recognition
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相關文章
- 1. An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 2. 【論文翻譯】An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 3. paper reading：Part-based Graph Convolutional Network for Action Recognition
- 4. DDGCN: A Dynamic Directed Graph Convolutional Network for Action Recognition
- 5. Self-Attention Network for Skeleton-based Human Action Recognition
- 6. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
- 7. 譯：Convolutional Two-Stream Network Fusion for Video Action Recognition
- 8. Part-based Graph Convolutional Network for Action Recognition論文筆記
- 9. [行爲識別]RPAN：An end-to-end recurrent pose-attention network for action recognition
- 10. Action Recognition Using Attention-Joints Graph Convolutional Neural Networks翻譯