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 361–370 of 517 papers

TitleStatusHype
A Noncontact Technique for Wave Measurement Based on Thermal Stereography and Deep Learning—0
A novel stereo matching pipeline with robustness and unfixed disparity search range—0
An underwater binocular stereo matching algorithm based on the best search domain—0
A Review of Vegetation Encroachment Detection in Power Transmission Lines using Optical Sensing Satellite Imagery—0
A Robust Real-Time Computing-based Environment Sensing System for Intelligent Vehicle—0
A shallow feature extraction network with a large receptive field for stereo matching tasks—0
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation—0
Automated 3D recovery from very high resolution multi-view satellite images—0
Automatic generation of realistic training data for learning parallel-jaw grasping from synthetic stereo images—0
A Weighted Sparse Coding Framework for Saliency Detection—0
Show:102550
← PrevPage 37 of 52Next →

No leaderboard results yet.