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Monocular contextual constraint for stereo matching with adaptive weights assignment

文献类型：期刊论文

作者Zhang, Chenghao3,4; Meng, Gaofeng2,3,4; Su, Bing1; Xiang, Shiming3,4; Pan, Chunhong3
刊名IMAGE AND VISION COMPUTING
出版日期2022-05-01
卷号121页码:10
ISSN号0262-8856
关键词Deep learning Stereo matching Monocular contextual constraint Adaptive weights assignment
DOI10.1016/j.imavis.2022.104424
通讯作者Meng, Gaofeng(gfmeng@nlpr.ia.ac.cn)
英文摘要Matching-based stereo disparity estimation has difficulty in dealing with occlusion, weak and repetitive textures in binocular vision. By contrast, monocular vision, estimating depth from a single image, is not subject to these challenges. Inspired by this, in this study, we propose an adaptive co-learning framework with monocular and stereo branches named CLStereo to improve stereo performance. This framework introduces a monocular branch as contextual constraints to transfer the prior knowledge learned from the monocular branch to the stereo branch. An adaptive weights assignment is further proposed to balance the co-learning of both branches without mutually tuning. CLStereo can be seamlessly embedded into many existing deep stereo models to boost their performance, especially in occluded, weak, and repetitive texture areas. Extensive experiments demonstrate that we achieve the state-of-the-art performance on the Scene Flow dataset and improve deep stereo models by at least 4% on KITTI 2012 and 2015 benchmarks. (c) 2022 Elsevier B.V. All rights reserved.
资助项目National Key Research and De-velopment Program of China[2020AAA0109702] ; National Natural Science Foundation of China[61976208] ; National Natural Science Foundation of China[61802407] ; National Natural Science Foundation of China[62071466]
WOS研究方向Computer Science ; Engineering ; Optics
语种英语
出版者ELSEVIER
WOS记录号WOS:000783099100003
资助机构National Key Research and De-velopment Program of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/48344]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
通讯作者Meng, Gaofeng
作者单位1.Renmin Univ China, Gaoling Sch Artificial Intelligence, Beijing 100872, Peoples R China
2.Chinese Acad Sci, HK Inst Sci & Innovat, Ctr Artificial Intelligence & Robot, Hong Kong 999077, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Chenghao,Meng, Gaofeng,Su, Bing,et al. Monocular contextual constraint for stereo matching with adaptive weights assignment[J]. IMAGE AND VISION COMPUTING,2022,121:10.
APA Zhang, Chenghao,Meng, Gaofeng,Su, Bing,Xiang, Shiming,&Pan, Chunhong.(2022).Monocular contextual constraint for stereo matching with adaptive weights assignment.IMAGE AND VISION COMPUTING,121,10.
MLA Zhang, Chenghao,et al."Monocular contextual constraint for stereo matching with adaptive weights assignment".IMAGE AND VISION COMPUTING 121(2022):10.

入库方式： OAI收割

来源：自动化研究所

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