《Real-time 2D Multi-Person Pose Estimation on CPU：Lightweight OpenPose》論文筆記
參考代碼：lightweight-human-pose-estimation.pytorch 1. 概述 導讀：這篇文章是在OpenPose的基礎上進行輕量化改進，從而使得整體網絡能在Intel的CPU上達到實時的運行效果。對此文章的算法也是相當輕量級的只有410w的參數90億的浮點運算，是含有兩階段優化OpenPose的15%，但是其AP（Average Precision）只降低了1個點。自然
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- 2. Openpose論文閱讀 | Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 3. openpose論文總結：Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
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- 8. OpenPose——Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
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- 10. # Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
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相關文章
- 1. 論文筆記：OpenPose（Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields）
- 2. Openpose論文閱讀 | Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 3. openpose論文總結：Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 4. 論文學習筆記：OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 5. 論文筆記二：OpenPose（Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields部分
- 6. Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 7. 2D Pose Estimation
- 8. OpenPose——Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 9. OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- 10. # Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields