Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
基于3d几何约束的无监督深度估计 文章发表在CVPR 2018 ，代码貌似未开源 摘要 此前的无监督的深度估计的方法大多是采用基于图像重建和基于梯度的损失，只考虑了局部像素点之间的关系，并未从整体上对深度进行约束。我们的主要贡献是明确考虑了场景的三维几何，提出一种三维几何约束，使得相邻帧之间估计出的点云和相机自运动保持一致。另外作者的方法也可以在自己用手机收集的数据集上进行训练。 Introduc
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- 2. 读论文1-Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric（老师让看）
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- 8. Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics 之论文详解
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相关文章
- 1. Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
- 2. 读论文1-Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric（老师让看）
- 3. 《Unsupervised Learning of Depth and Ego-Motion from Video》论文笔记
- 4. CVPR 2017【论文笔记】Unsupervised Learning of Depth and Ego-Motion from Video
- 5. Unsupervised Learning of Depth and Ego-Motion from Video论文见解
- 6. 景深 | Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
- 7. 论文笔记-深度估计(6)-Unsupervised Learning of Depth and Ego-Motion from Video
- 8. Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics 之论文详解
- 9. unsupervised learning of monocular depth estimation with bundle adjustment, Super-Resolution 论文
- 10. Depth from Videos in the Wild：Unsupervised Monocular Depth Learning from Unknown Cameras