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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 141150 of 517 papers

TitleStatusHype
Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty EstimationCode1
Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene CompletionCode1
A Simple Framework for 3D Occupancy Estimation in Autonomous DrivingCode2
Iterative Geometry Encoding Volume for Stereo MatchingCode2
UAVStereo: A Multiple Resolution Dataset for Stereo Matching in UAV ScenariosCode1
Visibility-Aware Pixelwise View Selection for Multi-View Stereo Matching0
A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images0
Inter-View Depth Consistency Testing in Depth Difference Subspace0
CGI-Stereo: Accurate and Real-Time Stereo Matching via Context and Geometry InteractionCode2
Parameterized Cost Volume for Stereo Matching0
Show:102550
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