RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation
單人pose模型文章，提出了一種基於kinematic structure來輔助模型對關鍵點進行定位，整體結構如下： 模型是一個仿U-Net結構的網絡結構，忽略U-Net的底部，先看下輸出，模型會在不同的scale下進行upsample到原圖分辨率大小進行heatmap輸出，所以是個包含有多個loss的網絡結構，重點看下上圖中的綠色部分，也即是文章提出的Kinematic Features Upd
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- 2. Fast Human Pose Estimation
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- 4. Deep globally constrained MRFs for Human Pose Estimation
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- 6. Learning Feature Pyramids for Human Pose Estimation（理解）
- 7. 《Multi-Context Attention for Human Pose Estimation》
- 8. March 11-Deep High-Resolution Representation Learning for Human Pose Estimation-paper reading
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相關文章
- 1. (34) RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation
- 2. Fast Human Pose Estimation
- 3. Deep High-Resolution Representation Learning for Human Pose Estimation
- 4. Deep globally constrained MRFs for Human Pose Estimation
- 5. Deep Learning Models and Code for Pose Estimation
- 6. Learning Feature Pyramids for Human Pose Estimation（理解）
- 7. 《Multi-Context Attention for Human Pose Estimation》
- 8. March 11-Deep High-Resolution Representation Learning for Human Pose Estimation-paper reading
- 9. Deep High-Resolution Representation Learning for Human Pose Estimation論文翻譯閱讀 - 2019CVPR
- 10. Deep High-Resolution Representation Learning for Human Pose Estimation論文翻譯