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Focusness guided salient object detection
Xiao Xiaolin; Zhou Yicong
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source Publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Conference DateOCT 05-08, 2017
Conference PlaceBanff, CANADA

Salient object detection aims to correctly highlight the most salient object(s) in an image. Combining fine-grained contrast prior with rough-grained object consistency, this paper proposes a Focusness Guided Salient object detection (FGS) algorithm. To obtain clean and precise contrast map, FGS uses the focusness prior to guide the contrast map. Combing different saliency priors, FGS utilizes a unified least-square framework to generate the final optimal salient map. Experiments demonstrate the proposed method outperforms the state-of-the-arts.

URLView the original
Indexed BySCIE
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000427598703089
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Faculty of Science and Technology
AffiliationUniversity of Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xiao Xiaolin,Zhou Yicong. Focusness guided salient object detection[C],2017:3462-3466.
APA Xiao Xiaolin,&Zhou Yicong.(2017).Focusness guided salient object detection.2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017,2017-January,3462-3466.
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