CASIA OpenIR  > 智能感知与计算研究中心
Feedback Convolutional Neural Network for Visual Localization and Segmentation
Cao, Chunshui1,2; Huang, Yongzhen3,4; Yang, Yi5; Wang, Liang3,4; Wang, Zilei1; Tan, Tieniu3,4
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN0162-8828
2019-07-01
Volume41Issue:7Pages:1627-1640
Corresponding AuthorCao, Chunshui(ccs@mail.ustc.edu.cn)
AbstractFeedback is a fundamental mechanism existing in the human visual system, but has not been explored deeply in designing computer vision algorithms. In this paper, we claim that feedback plays a critical role in understanding convolutional neural networks (CNNs), e.g., how a neuron in CNNs describes an object's pattern, and how a collection of neurons form comprehensive perception to an object. To model the feedback in CNNs, we propose a novel model named Feedback CNN and develop two new processing algorithms, i.e., neural pathway pruning and pattern recovering. We mathematically prove that the proposed method can reach local optimum. Note that Feedback CNN belongs to weakly supervised methods and can be trained only using category-level labels. But it possesses a powerful capability to accurately localize and segment category-specific objects. We conduct extensive visualization analysis, and the results reveal the close relationship between neurons and object parts in Feedback CNN. Finally, we evaluate the proposed Feedback CNN over the tasks of weakly supervised object localization and segmentation, and the experimental results on ImageNet and Pascal VOC show that our method remarkably outperforms the state-of-the-art ones.
Keywordfeedback convolutional neural networks (CNNs) weakly supervised object localization object segmentation
DOI10.1109/TPAMI.2018.2843329
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFB1001000] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[61420106015]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000470972300008
PublisherIEEE COMPUTER SOC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26028
Collection智能感知与计算研究中心
Corresponding AuthorCao, Chunshui
Affiliation1.Univ Sci & Technol China, Hefei 230000, Anhui, Peoples R China
2.Chinese Acad Sci CASIA, Ctr Res Intelligent Percept & Comp CRIPAC, NLPR, Inst Automat, Beijing 100864, Peoples R China
3.Univ Chinese Acad Sci, Huairou 101408, Peoples R China
4.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Inst Automat, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China
5.Baidu Res, Sunnyvale, CA 94089 USA
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Cao, Chunshui,Huang, Yongzhen,Yang, Yi,et al. Feedback Convolutional Neural Network for Visual Localization and Segmentation[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2019,41(7):1627-1640.
APA Cao, Chunshui,Huang, Yongzhen,Yang, Yi,Wang, Liang,Wang, Zilei,&Tan, Tieniu.(2019).Feedback Convolutional Neural Network for Visual Localization and Segmentation.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,41(7),1627-1640.
MLA Cao, Chunshui,et al."Feedback Convolutional Neural Network for Visual Localization and Segmentation".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 41.7(2019):1627-1640.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Cao, Chunshui]'s Articles
[Huang, Yongzhen]'s Articles
[Yang, Yi]'s Articles
Baidu academic
Similar articles in Baidu academic
[Cao, Chunshui]'s Articles
[Huang, Yongzhen]'s Articles
[Yang, Yi]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Cao, Chunshui]'s Articles
[Huang, Yongzhen]'s Articles
[Yang, Yi]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

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