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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

Showing 261270 of 517 papers

TitleStatusHype
Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation0
Stereo Object Matching Network0
YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D DetectionCode1
ORStereo: Occlusion-Aware Recurrent Stereo Matching for 4K-Resolution Images0
PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching0
ES-Net: An Efficient Stereo Matching NetworkCode1
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNsCode0
An underwater binocular stereo matching algorithm based on the best search domain0
3D Surface Reconstruction From Multi-Date Satellite ImagesCode1
Multi-Scale Cost Volumes Cascade Network for Stereo Matching0
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