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Stereo Object Matching Network [PDF]
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information. Unlike existing stereo matching methods that exclusively focus on the pixel-level correspondence between stereo images within a volumetric space (i.e., cost volume), we exploit this volumetric structure in
Jaesung Choe +3 more
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Bidirectional Stereo Matching Network With Double Cost Volumes
IEEE Access, 2021 In stereo matching, the high-quality cost volume is the key to improve the matching accuracy. Current stereo matching networks only use traditional methods or neural networks to generate one or more cost volumes.
Xiaogang Jia, Wei Chen, Zhengfa Liang
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Self-Supervised Stereo Matching Method Based on SRWP and PCAM for Urban Satellite Images
Remote Sensing, 2022 In this paper, we propose a self-supervised stereo matching method based on superpixel random walk pre-matching (SRWP) and parallax-channel attention mechanism (PCAM). Our method is divided into two stages, training and testing.
Wen Chen, Hao Chen, Shuting Yang
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IEEE Access, 2023 While stereo matching methods have great progress in recent years, they still face several formidable challenges. These challenges mainly include how to fully utilize global context and depth semantic information for depth feature extraction while ...
Bowen Jiao +4 more
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Dense spatio‐temporal stereo matching for intelligent driving systems
IET Image Processing, 2021 This paper addresses the problem of matching stereo images acquired by a stereo system mounted aboard an intelligent vehicle. The main idea behind the new method consists in involving temporal matching between a current stereo pair and its preceding one ...
Zakaria Kerkaou +3 more
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Computer Vision and Image Understanding, 2005 A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given the observed stereo images. A mixed sampling and deterministic strategy is adopted to balance between effectiveness and efficiency: the parameters are estimated via Markov ...
Li Cheng 0001, Terry Caelli
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Local Stereo Matching Based on Support Weight With Motion Flow for Dynamic Scene
IEEE Access, 2016 Stereo matching is one of the most important and challenging subjects in the field of stereo vision. The disparity obtained in stereo matching can represent depth information in 3-D world to a great extent and shows great importance in stereo field.
Jiachen Yang +5 more
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2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Stereo is a prominent technique to infer dense depth maps from images, and deep learning further pushed forward the state-of-the-art, making end-to-end architectures unrivaled when enough data is available for training. However, deep networks suffer from significant drops in accuracy when dealing with new environments.
M. Poggi +3 more
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IET Computer Vision, 2022 Stereo matching is an important computer vision tool for three‐dimensional (3D) positioning, 3D visual representation, precision detection and recognition with 3D information.
Chih‐Hsuan Huang, Jar‐Ferr Yang
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CoRR, 2014 Pattern Recognition (ICPR), 2012 21st International Conference ...
Kang Zhang 0004 +5 more
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