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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 301–350 of 517 papers

TitleStatusHype
UltraStereo: Efficient Learning-Based Matching for Active Stereo Systems—0
Uncertainty Estimation for End-To-End Learned Dense Stereo Matching via Probabilistic Deep Learning—0
Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching—0
Uniform Subdivision of Omnidirectional Camera Space for Efficient Spherical Stereo Matching—0
EMatch: A Unified Framework for Event-based Optical Flow and Stereo Matching—0
UniTT-Stereo: Unified Training of Transformer for Enhanced Stereo Matching—0
Unsupervised Deep Asymmetric Stereo Matching With Spatially-Adaptive Self-Similarity—0
Unsupervised Learning of Stereo Matching—0
Unsupervised monocular stereo matching—0
Using Orthophoto for Building Boundary Sharpening in the Digital Surface Model—0
UWStereo: A Large Synthetic Dataset for Underwater Stereo Matching—0
VHS: High-Resolution Iterative Stereo Matching with Visual Hull Priors—0
Virtual Blood Vessels in Complex Background using Stereo X-ray Images—0
Visibility-Aware Pixelwise View Selection for Multi-View Stereo Matching—0
Visually Imbalanced Stereo Matching—0
Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation—0
WaveletStereo: Learning Wavelet Coefficients of Disparity Map in Stereo Matching—0
Wide baseline stereo matching with convex bounded-distortion constraints—0
Wide Baseline Stereo Matching With Convex Bounded Distortion Constraints—0
Widening siamese architectures for stereo matching—0
NLCA-Net v2 for Stereo Matching in ECCV'20 Robust Vision Challenge—0
MSDC-Net: Multi-Scale Dense and Contextual Networks for Automated Disparity Map for Stereo Matching—0
Fully Parallel Architecture for Semi-global Stereo Matching with Refined Rank Method—0
DISCO: Depth Inference from Stereo using Context—0
MCPDepth: Omnidirectional Depth Estimation via Stereo Matching from Multi-Cylindrical Panoramas—0
Gaussian Mixture based Evidential Learning for Stereo Matching—0
2T-UNET: A Two-Tower UNet with Depth Clues for Robust Stereo Depth Estimation—0
3D Hand Pose Tracking and Estimation Using Stereo Matching—0
3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model—0
3D Reconstruction of Curvilinear Structures with Stereo Matching DeepConvolutional Neural Networks—0
3D Scene Geometry Estimation from 360^ Imagery: A Survey—0
A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images—0
Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?—0
Accurate Human Body Reconstruction for Volumetric Video—0
Accurate Optical Flow via Direct Cost Volume Processing—0
Achieving Domain Robustness in Stereo Matching Networks by Removing Shortcut Learning—0
A Closed-Form Solution to Tensor Voting: Theory and Applications—0
A Comparative Evaluation of SGM Variants (including a New Variant, tMGM) for Dense 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
A Comparison of Stereo-Matching Cost between Convolutional Neural Network and Census for Satellite Images—0
Adaptive Deconvolution-based stereo matching Net for Local Stereo Matching—0
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions—0
AdaStereo: An Efficient Domain-Adaptive Stereo Matching Approach—0
AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching—0
ADCPNet: Adaptive Disparity Candidates Prediction Network for Efficient Real-Time Stereo Matching—0
A Deep Visual Correspondence Embedding Model for Stereo Matching Costs—0
A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images—0
Advancing Applications of Satellite Photogrammetry: Novel Approaches for Built-up Area Modeling and Natural Environment Monitoring using Stereo/Multi-view Satellite Image-derived 3D Data—0
A Learned Stereo Depth System for Robotic Manipulation in Homes—0
A Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching—0
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