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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 76–100 of 517 papers

TitleStatusHype
ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching NetworksCode1
Discrete Time Convolution for Fast Event-Based StereoCode1
Stereoscopic Universal Perturbations across Different Architectures and DatasetsCode1
PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense ReconstructionCode1
TriStereoNet: A Trinocular Framework for Multi-baseline Disparity EstimationCode1
Stereo Hybrid Event-Frame (SHEF) Cameras for 3D PerceptionCode1
Rational Polynomial Camera Model Warping for Deep Learning Based Satellite Multi-View Stereo MatchingCode1
Learning Signed Distance Field for Multi-view Surface ReconstructionCode1
MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingCode1
LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D DetectorCode1
Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume ExcitationCode1
Neural Rays for Occlusion-aware Image-based RenderingCode1
Bilateral Grid Learning for Stereo Matching NetworksCode1
ResDepth: A Deep Residual Prior For 3D Reconstruction From High-resolution Satellite ImagesCode1
SRH-Net: Stacked Recurrent Hourglass Network for Stereo MatchingCode1
Stereo Matching Based on Visual Sensitive InformationCode1
CFNet: Cascade and Fused Cost Volume for Robust Stereo MatchingCode1
SMD-Nets: Stereo Mixture Density NetworksCode1
YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D DetectionCode1
ES-Net: An Efficient Stereo Matching NetworkCode1
3D Surface Reconstruction From Multi-Date Satellite ImagesCode1
On the confidence of stereo matching in a deep-learning era: a quantitative evaluationCode1
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow EstimationCode1
Hierarchical Neural Architecture Search for Deep Stereo MatchingCode1
Matching-space Stereo Networks for Cross-domain GeneralizationCode1
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