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Depth Estimation

1229 directly classified papers

Papers per year

Papers

Point-Based Multi-View Stereo Network ICCV 2019
Real-Time Self-Adaptive Deep Stereo CVPR 2019
Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More CVPR 2019
Geometry-Aware Distillation for Indoor Semantic Segmentation CVPR 2019
DeepLiDAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene From Sparse LiDAR Data and Single Color Image CVPR 2019
Depth-Aware Video Frame Interpolation CVPR 2019
Learning to Minify Photometric Stereo CVPR 2019
Learning Non-Volumetric Depth Fusion Using Successive Reprojections CVPR 2019
Single Image Depth Estimation Trained via Depth From Defocus Cues CVPR 2019
Learning to Adapt for Stereo CVPR 2019
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation CVPR 2019
Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge CVPR 2019
StereoDRNet: Dilated Residual StereoNet CVPR 2019
CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth CVPR 2019
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation CVPR 2019
Learning Parallax Attention for Stereo Image Super-Resolution CVPR 2019
Multi-View Stereo by Temporal Nonparametric Fusion ICCV 2019
Depth Completion From Sparse LiDAR Data With Depth-Normal Constraints ICCV 2019
Learning Object-Specific Distance From a Monocular Image ICCV 2019
Enforcing Geometric Constraints of Virtual Normal for Depth Prediction ICCV 2019
FrameNet: Learning Local Canonical Frames of 3D Surfaces From a Single RGB Image ICCV 2019
Spatial Correspondence With Generative Adversarial Network: Learning Depth From Monocular Videos ICCV 2019
Surface Normals and Shape From Water ICCV 2019
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments ICCV 2019
Learning the Depths of Moving People by Watching Frozen People CVPR 2019