論文閱讀: 3D Human Pose Estimation in the Wild by Adversarial Learning
論文地址:https://arxiv.org/abs/1803.09722 出自港中文,CUHK-SenseTime Joint Lab 一、總體框架描述 1.本篇論文主體思路是提出了一個對抗性的學習框架，如下圖1所示： 圖1主體框架 2.生成
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- 1. DensePose: Dense Human Pose Estimation In The Wild
- 2. 【轉】DensePose: Dense Human Pose Estimation In The Wild
- 3. Whole-Body Human Pose Estimation in the Wild
- 4. 《Ordinal Depth Supervision for 3D Human Pose Estimation》-CVPR2018 論文閱讀
- 5. 【論文閱讀筆記】Towards Accurate Multi-person Pose Estimation in the Wild
- 6. 論文閱讀：《Towards accurate multi-person pose estimation in the wild》CVPR 2017
- 7. 論文閱讀：G-RMI：Towards accurate multi-person pose estimation in the wild——2017CVPR
- 8. 3D Human Pose Estimation = 2D Pose Estimation + Matching(2017)
- 9. 論文閱讀理解 - Learning Feature Pyramids for Human Pose Estimation
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相關文章
- 1. DensePose: Dense Human Pose Estimation In The Wild
- 2. 【轉】DensePose: Dense Human Pose Estimation In The Wild
- 3. Whole-Body Human Pose Estimation in the Wild
- 4. 《Ordinal Depth Supervision for 3D Human Pose Estimation》-CVPR2018 論文閱讀
- 5. 【論文閱讀筆記】Towards Accurate Multi-person Pose Estimation in the Wild
- 6. 論文閱讀：《Towards accurate multi-person pose estimation in the wild》CVPR 2017
- 7. 論文閱讀：G-RMI：Towards accurate multi-person pose estimation in the wild——2017CVPR
- 8. 3D Human Pose Estimation = 2D Pose Estimation + Matching(2017)
- 9. 論文閱讀理解 - Learning Feature Pyramids for Human Pose Estimation
- 10. Deep High-Resolution Representation Learning for Human Pose Estimation論文翻譯閱讀 - 2019CVPR