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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 4150 of 517 papers

TitleStatusHype
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions0
Segmentation-aware Prior Assisted Joint Global Information Aggregated 3D Building Reconstruction0
Self-Assessed Generation: Trustworthy Label Generation for Optical Flow and Stereo Matching in Real-worldCode1
A Lightweight Target-Driven Network of Stereo Matching for Inland WaterwaysCode0
Analysis of different disparity estimation techniques on aerial stereo image datasets0
The Sampling-Gaussian for stereo matching0
Pseudo-Stereo Inputs: A Solution to the Occlusion Challenge in Self-Supervised Stereo MatchingCode1
Match Stereo Videos via Bidirectional Alignment0
Event-based Stereo Depth Estimation: A SurveyCode2
Robust and Flexible Omnidirectional Depth Estimation with Multiple 360° Cameras0
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