SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 517 papers

TitleStatusHype
Matching-space Stereo Networks for Cross-domain GeneralizationCode1
Adaptive confidence thresholding for monocular depth estimationCode1
Parallax Attention for Unsupervised Stereo Correspondence LearningCode1
Stereo Plane SLAM Based on Intersecting LinesCode1
Learning Stereo Matchability in Disparity Regression NetworksCode1
Learning Stereo from Single ImagesCode1
HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo MatchingCode1
A Multi-spectral Dataset for Evaluating Motion Estimation SystemsCode1
MTStereo 2.0: improved accuracy of stereo depth estimation withMax-treesCode1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingCode1
PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo MatchingCode1
Epipolar TransformersCode1
StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo MatchingCode1
Deep 3D Portrait from a Single ImageCode1
AANet: Adaptive Aggregation Network for Efficient Stereo MatchingCode1
Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo MatchingCode1
Superpixel Segmentation with Fully Convolutional NetworksCode1
FADNet: A Fast and Accurate Network for Disparity EstimationCode1
Scene Completeness-Aware Lidar Depth Completion for Driving ScenarioCode1
Active Perception with A Monocular Camera for Multiscopic VisionCode1
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo MatchingCode1
GA-Net: Guided Aggregation Net for End-to-end Stereo MatchingCode1
Group-wise Correlation Stereo NetworkCode1
ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo SystemsCode1
Pyramid Stereo Matching NetworkCode1
Show:102550
← PrevPage 5 of 21Next →

No leaderboard results yet.