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 76–100 of 517 papers

TitleStatusHype
Bilateral Grid Learning for Stereo Matching NetworksCode1
A Multi-spectral Dataset for Evaluating Motion Estimation SystemsCode1
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo MatchingCode1
BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgeryCode1
GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented FeatureCode1
Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching TransformerCode1
Hierarchical Neural Architecture Search for Deep Stereo MatchingCode1
FADNet: A Fast and Accurate Network for Disparity EstimationCode1
BDIS: Bayesian Dense Inverse Searching Method for Real-Time Stereo Surgical Image MatchingCode1
CFNet: Cascade and Fused Cost Volume for Robust Stereo MatchingCode1
Diving into the Fusion of Monocular Priors for Generalized Stereo MatchingCode1
Do End-to-end Stereo Algorithms Under-utilize Information?Code1
Deep Laparoscopic Stereo Matching with TransformersCode1
Learning Stereo Matchability in Disparity Regression NetworksCode1
Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty EstimationCode1
Disparity Estimation Using a Quad-Pixel SensorCode1
Lightweight Multi-Drone Detection and 3D-Localization via YOLOCode1
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow EstimationCode1
MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingCode1
ELFNet: Evidential Local-global Fusion for Stereo MatchingCode1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingCode1
Multi-Label Stereo Matching for Transparent Scene Depth EstimationCode1
Depth Estimation by Combining Binocular Stereo and Monocular Structured-LightCode1
Neural Rays for Occlusion-aware Image-based RenderingCode1
Digging Into Uncertainty-based Pseudo-label for Robust Stereo MatchingCode1
Show:102550
← PrevPage 4 of 21Next →

No leaderboard results yet.