【论文笔记】Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
【论文笔记】可能对称可变形3D物体自然场景下图像的无监督学习 CVPR 2020中，无监督学习或者半监督学习也是一个热点话题。 本期，推送一篇CVPR 2020中可能对称可变形的3D物体自然场景下图像的无监督学习。 论文题目：Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wi
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相关文章
- 1. 【论文阅读】Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
- 2. [三维重建] Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
- 3. 【论文笔记】Learning from Synthetic Data for Crowd Counting in the Wild
- 4. 景深 | Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
- 5. 论文笔记（三） 【Learning from Simulated and Unsupervised Images through Adversarial Training】
- 6. Deep Learning 论文笔记 (3): Deep Learning Face Attributes in the Wild
- 7. 论文阅读: 3D Human Pose Estimation in the Wild by Adversarial Learning
- 8. Learning to Detect Fake Face Images in the Wild
- 9. Material Recognition in the Wild with the Materials in Context Database论文笔记
- 10. 论文笔记：Learning Denoising from Single Noisy Images