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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

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Showing 101–125 of 517 papers

TitleStatusHype
Modeling Stereo-Confidence Out of the End-to-End Stereo-Matching Network via Disparity Plane Sweep—0
S^3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving—0
Dense 3D Reconstruction Through Lidar: A Comparative Study on Ex-vivo Porcine Tissue—0
3D Scene Geometry Estimation from 360^ Imagery: A Survey—0
Left-right Discrepancy for Adversarial Attack on Stereo Networks—0
RomniStereo: Recurrent Omnidirectional Stereo MatchingCode0
S3Net: Innovating Stereo Matching and Semantic Segmentation with a Single-Branch Semantic Stereo Network in Satellite Epipolar ImageryCode1
LoS: Local Structure-Guided Stereo Matching—0
Quantum-Hybrid Stereo Matching With Nonlinear Regularization and Spatial Pyramids—0
BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgeryCode1
Global Occlusion-Aware Transformer for Robust Stereo MatchingCode1
Quantum Annealing for Computer Vision Minimization Problems—0
Color Agnostic Cross-Spectral Disparity EstimationCode0
Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain GeneralizationCode1
Instance-aware Multi-Camera 3D Object Detection with Structural Priors Mining and Self-Boosting Learning—0
OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong BaselineCode0
Phase Guided Light Field for Spatial-Depth High Resolution 3D Imaging—0
Polarimetric PatchMatch Multi-View Stereo—0
MC-Stereo: Multi-peak Lookup and Cascade Search Range for Stereo MatchingCode1
HeightFormer: A Multilevel Interaction and Image-adaptive Classification-regression Network for Monocular Height Estimation with Aerial Images—0
Skin the sheep not only once: Reusing Various Depth Datasets to Drive the Learning of Optical Flow—0
RSRD: A Road Surface Reconstruction Dataset and Benchmark for Safe and Comfortable Autonomous Driving—0
When Epipolar Constraint Meets Non-local Operators in Multi-View StereoCode1
Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration—0
Learning Parallax for Stereo Event-based Motion Deblurring—0
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