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Stereo Matching Hand

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Showing 26–50 of 163 papers

TitleStatusHype
A Deep Visual Correspondence Embedding Model for Stereo Matching Costs—0
Confidence Inference for Focused Learning in Stereo Matching—0
A Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching—0
AMNet: Deep Atrous Multiscale Stereo Disparity Estimation Networks—0
CV-HAZOP: Introducing Test Data Validation for Computer Vision—0
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs—0
Analysis of critical parameters of satellite stereo image for 3D reconstruction and mapping—0
Analyzing Computer Vision Data - The Good, the Bad and the Ugly—0
Deep Stereo Matching with Dense CRF Priors—0
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture—0
Automated 3D recovery from very high resolution multi-view satellite images—0
Depth from Monocular Images using a Semi-Parallel Deep Neural Network (SPDNN) Hybrid Architecture—0
Depth From Semi-Calibrated Stereo and Defocus—0
Depth Map Estimation and Colorization of Anaglyph Images Using Local Color Prior and Reverse Intensity Distribution—0
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network—0
Depth Reconstruction from Sparse Samples: Representation, Algorithm, and Sampling—0
Detecting Ground Control Points via Convolutional Neural Network for Stereo Matching—0
Cascaded multi-scale and multi-dimension convolutional neural network for stereo matching—0
Direction Matters: Depth Estimation With a Surface Normal Classifier—0
Direct Monocular Odometry Using Points and Lines—0
Discrete MRF Inference of Marginal Densities for Non-uniformly Discretized Variable Space—0
DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios—0
CATS: A Color and Thermal Stereo Benchmark—0
DSVO: Direct Stereo Visual Odometry—0
DISCO: Depth Inference from Stereo using Context—0
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