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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 321330 of 517 papers

TitleStatusHype
Geometry-Aware Unsupervised Domain Adaptation for Stereo Matching0
Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving0
Ghost-Stereo: GhostNet-based Cost Volume Enhancement and Aggregation for Stereo Matching Networks0
Gradient-based Camera Exposure Control for Outdoor Mobile Platforms0
Graph Cut based Continuous Stereo Matching using Locally Shared Labels0
Gromov-Wasserstein Problem with Cyclic Symmetry0
HeightFormer: A Multilevel Interaction and Image-adaptive Classification-regression Network for Monocular Height Estimation with Aerial Images0
Appearance and Shape from Water Reflection0
Shift Convolution Network for Stereo Matching0
Simultaneous Video Defogging and Stereo Reconstruction0
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