Hierarchical Edge Refinement Network for Saliency Detection | |
Song, Dawei3,4; Dong, Yongsheng1,2; Li, Xuelong1,2 | |
刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
2021 | |
卷号 | 30页码:7567-7577 |
关键词 | Image edge detection Feature extraction Saliency detection Data mining Convolution Semantics Visualization Saliency detection edge preserving network atrous spatial pyramid pooling module one-to-one hierarchical supervision strategy |
ISSN号 | 1057-7149;1941-0042 |
DOI | 10.1109/TIP.2021.3106798 |
产权排序 | 1 |
英文摘要 | At present, most saliency detection methods are based on fully convolutional neural networks (FCNs). However, FCNs usually blur the edges of salient objects. Due to that, the multiple convolution and pooling operations of the FCNs will limit the spatial resolution of the feature maps. To alleviate this issue and obtain accurate edges, we propose a hierarchical edge refinement network (HERNet) for accurate saliency detection. In detail, the HERNet is mainly composed of a saliency prediction network and an edge preserving network. Firstly, the saliency prediction network is used to roughly detect the regions of salient objects and is based on a modified U-Net structure. Then, the edge preserving network is used to accurately detect the edges of salient objects, and this network is mainly composed of the atrous spatial pyramid pooling (ASPP) module. Different from the previous indiscriminate supervision strategy, we adopt a new one-to-one hierarchical supervision strategy to supervise the different outputs of the entire network. Experimental results on five traditional benchmark datasets demonstrate that the proposed HERNet performs well when compared with the state-of-the-art methods. |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000693758500004 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/95068] |
专题 | 海洋光学技术研究室 |
通讯作者 | Li, Xuelong |
作者单位 | 1.Northwestern Polytech Univ, Minist Ind & Informat Technol, Key Lab Intelligent Interact & Applicat, Xian 710072, Peoples R China 2.Northwestern Polytech Univ, Sch Artificial Intelligence Opt & Elect iOPEN, Xian 710072, Peoples R China 3.Univ Chinese Acad Sci, Sch Optoelect, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Shaanxi Key Lab Ocean Opt, Xian 710119, Peoples R China |
推荐引用方式 GB/T 7714 | Song, Dawei,Dong, Yongsheng,Li, Xuelong. Hierarchical Edge Refinement Network for Saliency Detection[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2021,30:7567-7577. |
APA | Song, Dawei,Dong, Yongsheng,&Li, Xuelong.(2021).Hierarchical Edge Refinement Network for Saliency Detection.IEEE TRANSACTIONS ON IMAGE PROCESSING,30,7567-7577. |
MLA | Song, Dawei,et al."Hierarchical Edge Refinement Network for Saliency Detection".IEEE TRANSACTIONS ON IMAGE PROCESSING 30(2021):7567-7577. |
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