CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Multiview Label Sharing for Visual Representations and Classifications
Zhang, Chunjie1,2; Cheng, Jian2,3,4; Tian, Qi5
AbstractDifferent views represent different aspects of images. It is more effective to combine them for visual classifications. This paper proposes a novel multiview label sharing method to combine the discriminative power of different views for classifications. Especially, we linearly transfer different views into a shared space for representations. The inter-view similarities are kept in the shared space for each view. We also ensure the intra-view similarities of the same class between different views are preserved in the shared space. We jointly learn the classifiers and transformation matrices by minimizing the summed classification loss along with the inter-view and intra-view similarity constraints. In this paper, the inter-view constraints refer to the similarities between images of the corresponding view, whereas the intra-view constraints refer to the similarities between different views of images with the same semantics. Experimental results and analysis on several public datasets show the effectiveness of the proposed multiview label sharing method for visual classifications.
KeywordMulti-view Learning Linear Transformation Shared Space Image Representation Visual Classification
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61303154 ; Scientific Research Key Program of Beijing Municipal Commission of Education(KZ201610005012) ; ARO Grant(W911NF-15-1-0290) ; NEC Laboratories of America ; Blippar ; National Science Foundation of China(61429201) ; 61332016)
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000427623000011
Citation statistics
Cited Times:20[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Chunjie,Cheng, Jian,Tian, Qi. Multiview Label Sharing for Visual Representations and Classifications[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(4):903-913.
APA Zhang, Chunjie,Cheng, Jian,&Tian, Qi.(2018).Multiview Label Sharing for Visual Representations and Classifications.IEEE TRANSACTIONS ON MULTIMEDIA,20(4),903-913.
MLA Zhang, Chunjie,et al."Multiview Label Sharing for Visual Representations and Classifications".IEEE TRANSACTIONS ON MULTIMEDIA 20.4(2018):903-913.
Files in This Item: Download All
File Name/Size DocType Version Access License
08059841.pdf(615KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang, Chunjie]'s Articles
[Cheng, Jian]'s Articles
[Tian, Qi]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang, Chunjie]'s Articles
[Cheng, Jian]'s Articles
[Tian, Qi]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang, Chunjie]'s Articles
[Cheng, Jian]'s Articles
[Tian, Qi]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 08059841.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.