每天一篇论文 339/365 Geometry meets semantics for semi-supervised monocular depth estimation
Geometry meets semantics for semi-supervised monocular depth estimation 摘要 从单个图像进行深度估计是计算机视觉中一个非常激动人心的挑战。虽然其他基于图像的深度传感技术利用不同视点之间的几何结构（例如，来自运动的立体或结构），但是在单个图像中缺少这些线索会使单目深度估计任务变得不适定。为了便于推断，用于单目深度估计的最新编码器
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相关文章
- 1. 每天一篇论文 301/365 3D Packing for Self-Supervised Monocular Depth Estimation
- 2. 每天一篇论文 Geometric Pretraining for Monocular Depth Estimation
- 3. 每天一篇论文 SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation
- 4. 每天一篇论文 306/365Self-supervised Learning for Single View Depth and Surface Normal Estimation
- 5. 每天一篇论文 334/365 Don’t Forget The Past: Recurrent Depth Estimation from Monocular Video
- 6. # 每天一篇论文 254/365 Two-View Monocular Depth Estimation by Optic-Flow-Weighted Fusion
- 7. 每天一篇论文 360/365 Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
- 8. 每天一篇论文 276/365 Monocular Depth Estimation in New Environments With Absolute Scale
- 9. 每天一篇论文 343/365 Pyiredicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation
- 10. Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics 之论文详解