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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 271280 of 517 papers

TitleStatusHype
Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors0
StereoFlowGAN: Co-training for Stereo and Flow with Unsupervised Domain Adaptation0
Stereo Frustums: A Siamese Pipeline for 3D Object Detection0
StereoGen: High-quality Stereo Image Generation from a Single Image0
Stereo Matching by Joint Energy Minimization0
Stereo Matching by Self-supervision of Multiscopic Vision0
Stereo Matching in Time: 100+ FPS Video Stereo Matching for Extended Reality0
Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency0
Stereo Matching With Color and Monochrome Cameras in Low-Light Conditions0
Stereo Matching With Color-Weighted Correlation, Hierarchical Belief Propagation And Occlusion Handling0
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