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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 201210 of 517 papers

TitleStatusHype
ChiTransformer:Towards Reliable Stereo from CuesCode1
Attention Concatenation Volume for Accurate and Efficient Stereo MatchingCode2
Mixed Reality Depth Contour Occlusion Using Binocular Similarity Matching and Three-dimensional Contour Optimisation0
Accurate Human Body Reconstruction for Volumetric Video0
Light Robust Monocular Depth Estimation For Outdoor Environment Via Monochrome And Color Camera Fusion0
LiDAR-guided Stereo Matching with a Spatial Consistency Constraint0
Lightweight Multi-Drone Detection and 3D-Localization via YOLOCode1
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation0
Multi-Resolution Factor Graph Based Stereo Correspondence Algorithm0
Stereo Matching with Cost Volume based Sparse Disparity Propagation0
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