ReDA: Reinforced Differentiable Attribute for 3D Face Reconstruction
ReDA: Reinforced Differentiable Attribute for 3D Face Reconstruction 創新點： 1、針對3D人臉重建渲染成圖片的約束只有2d image 的 color 屬性問題，擴充爲color + depth + face_parsing_mask 2、針對使用Z-buffer渲染（在cnn中不屬於真正的可微分渲染）問題，提出使用CNN的操作
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- 1. Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
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相關文章
- 1. Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
- 2. 3D Face Reconstruction from a Single Image
- 3. 3D【11】人臉重建：Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition
- 4. Large Pose 3D Face Reconstruction 文章理解
- 5. End-to-end 3D face reconstruction with deep neural networks
- 6. Learning Residual Images for Face Attribute Manipulation
- 7. 人臉對齊（十八）--Joint Face Alignment and 3D Face Reconstruction
- 8. SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
- 9. Dummy 3D Reconstruction
- 10. Multi-View 3D Reconstruction