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 311–320 of 517 papers

TitleStatusHype
NLCA-Net v2 for Stereo Matching in ECCV'20 Robust Vision Challenge—0
Stereo Frustums: A Siamese Pipeline for 3D Object Detection—0
EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual—0
Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving—0
A Review of Vegetation Encroachment Detection in Power Transmission Lines using Optical Sensing Satellite Imagery—0
High-precision target positioning system for unmanned vehicles based on binocular vision—0
Adjusting Bias in Long Range Stereo Matching: A semantics guided approach—0
End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences—0
Cross-Modality 3D Object Detection—0
Stereo Event-based Particle Tracking Velocimetry for 3D Fluid Flow ReconstructionCode0
Show:102550
← PrevPage 32 of 52Next →

No leaderboard results yet.