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Stereo Matching

24 papers with code · Computer Vision

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Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

20 Oct 2015jzbontar/mc-cnn

We approach the problem by learning a similarity measure on small image patches using a convolutional neural network.

STEREO MATCHING

Pyramid Stereo Matching Network

CVPR 2018 JiaRenChang/PSMNet

The spatial pyramid pooling module takes advantage of the capacity of global context information by aggregating context in different scales and locations to form a cost volume.

DEPTH ESTIMATION STEREO MATCHING

Learning for Disparity Estimation through Feature Constancy

CVPR 2018 JiaRenChang/PSMNet

The second part performs matching cost calculation, matching cost aggregation and disparity calculation to estimate the initial disparity using shared features.

DISPARITY ESTIMATION STEREO MATCHING

Learning Depth with Convolutional Spatial Propagation Network

4 Oct 2018XinJCheng/CSPN

In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks.

DEPTH COMPLETION DEPTH ESTIMATION STEREO MATCHING

StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction

ECCV 2018 meteorshowers/StereoNet

A first estimate of the disparity is computed in a very low resolution cost volume, then hierarchically the model re-introduces high-frequency details through a learned upsampling function that uses compact pixel-to-pixel refinement networks.

DEPTH ESTIMATION QUANTIZATION STEREO MATCHING

Continuous 3D Label Stereo Matching using Local Expansion Moves

28 Mar 2016t-taniai/LocalExpStereo

The local expansion moves extend traditional expansion moves by two ways: localization and spatial propagation.

STEREO MATCHING

GA-Net: Guided Aggregation Net for End-To-End Stereo Matching

CVPR 2019 feihuzhang/GANet

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities.

STEREO MATCHING

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

CVPR 2019 feihuzhang/GANet

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities.

STEREO MATCHING

Cross-Scale Cost Aggregation for Stereo Matching

CVPR 2014 rookiepig/CrossScaleStereo

We firstly reformulate cost aggregation from a unified optimization perspective and show that different cost aggregation methods essentially differ in the choices of similarity kernels.

STEREO MATCHING

Group-wise Correlation Stereo Network

CVPR 2019 xy-guo/GwcNet

Previous works built cost volumes with cross-correlation or concatenation of left and right features across all disparity levels, and then a 2D or 3D convolutional neural network is utilized to regress the disparity maps.

AUTONOMOUS DRIVING STEREO MATCHING