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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 201–225 of 517 papers

TitleStatusHype
Dedge-AGMNet:an effective stereo matching network optimized by depth edge auxiliary task—0
A Robust Real-Time Computing-based Environment Sensing System for Intelligent Vehicle—0
A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images—0
Dense 3D Reconstruction Through Lidar: A Comparative Study on Ex-vivo Porcine Tissue—0
Degradation-agnostic Correspondence from Resolution-asymmetric Stereo—0
A Review of Vegetation Encroachment Detection in Power Transmission Lines using Optical Sensing Satellite Imagery—0
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture—0
An underwater binocular stereo matching algorithm based on the best search domain—0
Deep Stereo Matching with Dense CRF Priors—0
Deep Material-Aware Cross-Spectral Stereo Matching—0
Hyperspectral Light Field Stereo Matching—0
Deep Learning of Partial Graph Matching via Differentiable Top-K—0
A novel stereo matching pipeline with robustness and unfixed disparity search range—0
A Noncontact Technique for Wave Measurement Based on Thermal Stereography and Deep Learning—0
2T-UNET: A Two-Tower UNet with Depth Clues for Robust Stereo Depth Estimation—0
H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry—0
High-Resolution Depth Maps Based on TOF-Stereo Fusion—0
High-precision target positioning system for unmanned vehicles based on binocular vision—0
High-Frequency Stereo Matching Network—0
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs—0
HeightFormer: A Multilevel Interaction and Image-adaptive Classification-regression Network for Monocular Height Estimation with Aerial Images—0
HyperDepth: Learning Depth From Structured Light Without Matching—0
CV-HAZOP: Introducing Test Data Validation for Computer Vision—0
Gromov-Wasserstein Problem with Cyclic Symmetry—0
Cross-Modality 3D Object Detection—0
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