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Stereo Matching

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Arlo0o/StereoScene

공식 코드

Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion

https://github.com/Artifineuro/crl

공식 코드

Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching

https://github.com/Artifineuro/zole

공식 코드

Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains

https://github.com/BFZD233/TranScene

공식 코드

Multi-Label Stereo Matching for Transparent Scene Depth Estimation

https://github.com/DeepMotionAIResearch/DenseMatchingBenchmark

공식 코드

Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching

https://github.com/GhiXu/CIDER

공식 코드

Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume

https://github.com/HKBU-HPML/FADNet

공식 코드

FADNet: A Fast and Accurate Network for Disparity Estimation

https://github.com/JiaRenChang/PSMNet

공식 코드

Pyramid Stereo Matching Network

https://github.com/JingweiSong/BDIS

공식 코드

Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery

https://github.com/LongguangWang/PAM

공식 코드

Parallax Attention for Unsupervised Stereo Correspondence Learning

https://github.com/Magicboomliu/NINet

공식 코드

Digging Into Normal Incorporated Stereo Matching

https://github.com/NGCLAB/multi-spectral-dataset

공식 코드

A Multi-spectral Dataset for Evaluating Motion Estimation Systems

https://github.com/NVlabs/FoundationStereo

공식 코드

FoundationStereo: Zero-Shot Stereo Matching

https://github.com/Owen-Liuyuxuan/visualDet3D

공식 코드

YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection

https://github.com/Qjizhi/GenStereo

공식 코드

GenStereo: Towards Open-World Generation of Stereo Images and Unsupervised Matching

https://github.com/SBCV/SatelliteSurfaceReconstruction

공식 코드

3D Surface Reconstruction From Multi-Date Satellite Images

https://github.com/SibylGao/MSCVP-MVSNet

공식 코드

Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view Stereo

https://github.com/WangHewei16/Stereo-Matching

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Stereo Matching Based on Visual Sensitive Information

https://github.com/XinJCheng/CSPN

공식 코드

Learning Depth with Convolutional Spatial Propagation Network

https://github.com/XuelianCheng/LEAStereo

공식 코드

Hierarchical Neural Architecture Search for Deep Stereo Matching

https://github.com/XuelianCheng/LidarStereoNet

공식 코드

Noise-Aware Unsupervised Deep Lidar-Stereo Fusion

https://github.com/YaoChengTang/Diving-into-the-Fusion-of-Monocular-Priors-for-Generalized-Stereo-Matching

공식 코드

Diving into the Fusion of Monocular Priors for Generalized Stereo Matching

https://github.com/aeolusguan/NMRF

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Neural Markov Random Field for Stereo Matching

https://github.com/alexklwong/stereoscopic-universal-perturbations

공식 코드

Stereoscopic Universal Perturbations across Different Architectures and Datasets

https://github.com/alibaba/cascade-stereo

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Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching

https://github.com/amitshaked/resmatch

공식 코드

Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning

https://github.com/antabangun/coex

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Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation

https://github.com/aryanshar/swarm-detection

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Lightweight Multi-Drone Detection and 3D-Localization via YOLO

https://github.com/autonomousvision/unimatch

공식 코드

Unifying Flow, Stereo and Depth Estimation

https://github.com/bartn8/eventvppstereo

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LiDAR-Event Stereo Fusion with Hallucinations

https://github.com/bartn8/stereoanywhere

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Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail

https://github.com/bartn8/vppdc

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Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization

https://github.com/ccj5351/DAFStereoNets

공식 코드

Do End-to-end Stereo Algorithms Under-utilize Information?

https://github.com/ccj5351/MS-Nets

공식 코드

Matching-space Stereo Networks for Cross-domain Generalization

https://github.com/changqiong/Z2ZNCC

공식 코드

Efficient stereo matching on embedded GPUs with zero-means cross correlation

https://github.com/choyingw/SCADC-DepthCompletion

공식 코드

Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

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