SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 261–270 of 517 papers

TitleStatusHype
LiDAR-guided Stereo Matching with a Spatial Consistency Constraint—0
Multi-Resolution Factor Graph Based Stereo Correspondence Algorithm—0
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation—0
Stereo Matching with Cost Volume based Sparse Disparity Propagation—0
Uniform Subdivision of Omnidirectional Camera Space for Efficient Spherical Stereo Matching—0
FoggyStereo: Stereo Matching With Fog Volume Representation—0
Continual Stereo Matching of Continuous Driving Scenes With Growing ArchitectureCode0
Sparse LiDAR Assisted Self-supervised Stereo Disparity Estimation—0
Depth Refinement for Improved Stereo Reconstruction—0
AdaStereo: An Efficient Domain-Adaptive Stereo Matching Approach—0
Show:102550
← PrevPage 27 of 52Next →

No leaderboard results yet.