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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
StereoGen: High-quality Stereo Image Generation from a Single Image0
Learned Binocular-Encoding Optics for RGBD Imaging Using Joint Stereo and Focus Cues0
Active Event-based Stereo VisionCode0
Gromov-Wasserstein Problem with Cyclic Symmetry0
Uncertainty Quantification in Stereo MatchingCode0
MobiFuse: A High-Precision On-device Depth Perception System with Multi-Data Fusion0
SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing0
All-in-One: Transferring Vision Foundation Models into Stereo Matching0
Stereo Anything: Unifying Stereo Matching with Large-Scale Mixed Data0
Superpixel Cost Volume Excitation for Stereo Matching0
Show:102550
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