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Salient object detection based on an efficient End-to-End Saliency Regression Network
Xi, Xuanyang1; Luo, Yongkang1; Wang, Peng1; Qiao, Hong1,2
发表期刊NEUROCOMPUTING
ISSN0925-2312
2019-01-05
卷号323页码:265-276
通讯作者Luo, Yongkang(yongkang.luo@ia.ac.cn)
摘要Salient object detection aims at detecting and segmenting the most salient objects from images or videos. It serves as a pre-processing step for a variety of computer vision and image processing tasks. Therefore, efficient and simple detection procedure is the primary requirement of salient object detection. Although many methods with impressive performances have been proposed, they always include complicated procedures. They are time-consuming and not easy to be applied in practical application. In order to address this issue, we propose an efficient and simple salient object detection architecture based on saliency regression network. Our method is a simplified end-to-end deep neural network without any pre-processing and post-processing. It can directly predict a dense full-resolution saliency map for a given image with a compact pipeline. Experimental results on five benchmark datasets show that the proposed method can achieve comparable or better precision performance than the state-of-the-art methods while get an improvement in the detection speed. (C) 2018 Elsevier B.V. All rights reserved.
关键词Salient object detection Saliency regression Deep convolutional neural networks Fully convolutional networks
DOI10.1016/j.neucom.2018.10.002
关键词[WOS]GRAPH
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[91748131] ; National Natural Science Foundation of China[U1613213] ; National Natural Science Foundation of China[61210009] ; National Natural Science Foundation of China[61602483] ; National Natural Science Foundation of China[61771471] ; National Natural Science Foundation of China[61702516] ; National Natural Science Foundation of China[61603389] ; National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; Youth Innovation Promotion Association of CAS[2015112]
项目资助者National Natural Science Foundation of China ; National Key Research and Development Program of China ; Youth Innovation Promotion Association of CAS
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000448945600022
出版者ELSEVIER SCIENCE BV
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22775
专题机器人理论与应用团队
通讯作者Luo, Yongkang
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
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Xi, Xuanyang,Luo, Yongkang,Wang, Peng,et al. Salient object detection based on an efficient End-to-End Saliency Regression Network[J]. NEUROCOMPUTING,2019,323:265-276.
APA Xi, Xuanyang,Luo, Yongkang,Wang, Peng,&Qiao, Hong.(2019).Salient object detection based on an efficient End-to-End Saliency Regression Network.NEUROCOMPUTING,323,265-276.
MLA Xi, Xuanyang,et al."Salient object detection based on an efficient End-to-End Saliency Regression Network".NEUROCOMPUTING 323(2019):265-276.
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