About

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

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Greatest papers with code

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 STEREO MATCHING HAND

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 STEREO MATCHING HAND

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 STEREO MATCHING HAND

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

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 STEREO MATCHING HAND

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 STEREO MATCHING HAND

Single View Stereo Matching

CVPR 2018 lawy623/SVS

The resulting model outperforms all the previous monocular depth estimation methods as well as the stereo block matching method in the challenging KITTI dataset by only using a small number of real training data.

Ranked #7 on Monocular Depth Estimation on KITTI Eigen split (using extra training data)

MONOCULAR DEPTH ESTIMATION STEREO MATCHING STEREO MATCHING HAND

Epipolar Transformers

CVPR 2020 yihui-he/epipolar-transformers

The intuition is: given a 2D location p in the current view, we would like to first find its corresponding point p' in a neighboring view, and then combine the features at p' with the features at p, thus leading to a 3D-aware feature at p. Inspired by stereo matching, the epipolar transformer leverages epipolar constraints and feature matching to approximate the features at p'.

Ranked #2 on 3D Human Pose Estimation on Human3.6M (using extra training data)

3D HUMAN POSE ESTIMATION 3D POSE ESTIMATION STEREO MATCHING

AANet: Adaptive Aggregation Network for Efficient Stereo Matching

CVPR 2020 haofeixu/aanet

Despite the remarkable progress made by learning based stereo matching algorithms, one key challenge remains unsolved.

STEREO MATCHING