[骨架動作識別]A New Representation of Skeleton Sequences for 3D Action Recognition
A New Representation of Skeleton Sequences for 3D Action Recognition CVPR 2017 本文的主要思想是將３d骨架座標轉換成圖片，然後再用卷積網絡提取特徵，時域上的特徵通過特殊的卷積核來提取，以達到時序記憶的目的。 一、主要方法 1.New Representation 每一段3d skeleton sequence都轉換成四張
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相關文章
- 1. 論文翻譯：A New Representation of Skeleton Sequences for 3D Action Recognition
- 2. [骨架動作識別]數據集
- 3. [骨架動作識別]STA-LSTM: Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data
- 4. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition(動作識別)
- 5. Representation Flow for Action Recognition
- 6. Self-Attention Network for Skeleton-based Human Action Recognition
- 7. 【CVPR2017，action recognition,動作識別】Quo Vadis, Action Recognition? A New Model and the Kinetics Datase...
- 8. Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
- 9. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
- 10. 動作識別——Multi-Model Domain Adaptation for Fine-Grained Action Recognition——CVPR2020 oral