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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 281290 of 517 papers

TitleStatusHype
Stereo Matching with Cost Volume based Sparse Disparity Propagation0
Stereo Object Matching Network0
Stereo on a budget0
Stereo Risk: A Continuous Modeling Approach to Stereo Matching0
StereoSnakes: Contour Based Consistent Object Extraction For Stereo Images0
StereoVAE: A lightweight stereo-matching system using embedded GPUs0
StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks0
Structural inference affects depth perception in the context of potential occlusion0
STS: Surround-view Temporal Stereo for Multi-view 3D Detection0
Sub-pixel matching method for low-resolution thermal stereo images0
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