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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 376–400 of 517 papers

TitleStatusHype
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
One-view occlusion detection for stereo matching with a fully connected CRF model—0
On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey—0
OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline—0
Open-World Stereo Video Matching with Deep RNN—0
ORStereo: Occlusion-Aware Recurrent Stereo Matching for 4K-Resolution Images—0
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation—0
Parameterized Cost Volume for Stereo Matching—0
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