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Stereo Matching

Stereo Matching is one of the core technologies in computer vision, which recovers 3D structures of real world from 2D images. It has been widely used in areas such as autonomous driving, augmented reality and robotics navigation. Given a pair of rectified stereo images, the goal of Stereo Matching is to compute the disparity for each pixel in the reference image, where disparity is defined as the horizontal displacement between a pair of corresponding pixels in the left and right images.

Source: Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching

Papers

Showing 111120 of 517 papers

TitleStatusHype
Depth-aware Volume Attention for Texture-less Stereo MatchingCode1
Learning Signed Distance Field for Multi-view Surface ReconstructionCode1
Discrete Time Convolution for Fast Event-Based StereoCode1
MTStereo 2.0: improved accuracy of stereo depth estimation withMax-treesCode1
Depth Estimation by Combining Binocular Stereo and Monocular Structured-LightCode1
Multi-Label Stereo Matching for Transparent Scene Depth EstimationCode1
Learning Stereo Matchability in Disparity Regression NetworksCode1
Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty EstimationCode1
Neural Rays for Occlusion-aware Image-based RenderingCode1
Pyramid Stereo Matching NetworkCode1
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