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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 201–250 of 517 papers

TitleStatusHype
Geometry-Aware Unsupervised Domain Adaptation for Stereo Matching—0
Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving—0
All-in-One: Transferring Vision Foundation Models into Stereo Matching—0
A Comparative Study on Deep-Learning Methods for Dense Image Matching of Multi-angle and Multi-date Remote Sensing Stereo Images—0
Fast 3D Point Cloud Denoising via Bipartite Graph Approximation & Total Variation—0
Comparison of Stereo Matching Algorithms for the Development of Disparity Map—0
3D Reconstruction of Curvilinear Structures with Stereo Matching DeepConvolutional Neural Networks—0
Light Field Stereo Matching Using Bilateral Statistics of Surface Cameras—0
Gromov-Wasserstein Problem with Cyclic Symmetry—0
Light Robust Monocular Depth Estimation For Outdoor Environment Via Monochrome And Color Camera Fusion—0
Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality—0
Expansion of Visual Hints for Improved Generalization in Stereo Matching—0
HeightFormer: A Multilevel Interaction and Image-adaptive Classification-regression Network for Monocular Height Estimation with Aerial Images—0
CV-HAZOP: Introducing Test Data Validation for Computer Vision—0
A Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching—0
Expanding Sparse Guidance for Stereo Matching—0
Event-Driven Stereo Matching for Real-Time 3D Panoramic Vision—0
High-precision target positioning system for unmanned vehicles based on binocular vision—0
CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching—0
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields—0
A Learned Stereo Depth System for Robotic Manipulation in Homes—0
HyperDepth: Learning Depth From Structured Light Without Matching—0
A Comparative Evaluation of SGM Variants (including a New Variant, tMGM) for Dense Stereo Matching—0
Epipolar Geometry Based On Line Similarity—0
iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform—0
Entropy-difference based stereo error detection—0
End-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching—0
End-to-end Learning of Cost-Volume Aggregation for Real-time Dense Stereo—0
Deep Stereo Matching with Dense CRF Priors—0
Innovative 3D Depth Map Generation From A Holoscopic 3D Image Based on Graph Cut Technique—0
3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model—0
Instantaneous Stereo Depth Estimation of Real-World Stimuli with a Neuromorphic Stereo-Vision Setup—0
End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences—0
Inter-View Depth Consistency Testing in Depth Difference Subspace—0
Into the Twilight Zone: Depth Estimation using Joint Structure-Stereo Optimization—0
End-to-End 3D Hand Pose Estimation from Stereo Cameras—0
CFDNet: A Generalizable Foggy Stereo Matching Network with Contrastive Feature Distillation—0
KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks—0
Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives—0
A Closed-Form Solution to Tensor Voting: Theory and Applications—0
MCPDepth: Omnidirectional Depth Estimation via Stereo Matching from Multi-Cylindrical Panoramas—0
Learning Adaptive Dense Event Stereo From the Image Domain—0
Learning Dense Stereo Matching for Digital Surface Models from Satellite Imagery—0
Learning Dense Wide Baseline Stereo Matching for People—0
Depth Estimation Analysis of Orthogonally Divergent Fisheye Cameras with Distortion Removal—0
A Robust Real-Time Computing-based Environment Sensing System for Intelligent Vehicle—0
CATS: A Color and Thermal Stereo Benchmark—0
Learning Intra-view and Cross-view Geometric Knowledge for Stereo Matching—0
Efficient High-Resolution Stereo Matching using Local Plane Sweeps—0
Left-Right Comparative Recurrent Model for Stereo Matching—0
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