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Detection of Co-salient Objects by Looking Deep and Wide
Zhang, Dingwen1; Han, Junwei1; Li, Chao1; Wang, Jingdong2; Li, Xuelong3; Han, JW
作者部门光学影像学习与分析中心
2016-11-01
发表期刊INTERNATIONAL JOURNAL OF COMPUTER VISION
ISSN0920-5691
卷号120期号:2页码:215-232
产权排序3
摘要

In this paper, we propose a unified co-salient object detection framework by introducing two novel insights: (1) looking deep to transfer higher-level representations by using the convolutional neural network with additional adaptive layers could better reflect the sematic properties of the co-salient objects; (2) looking wide to take advantage of the visually similar neighbors from other image groups could effectively suppress the influence of the common background regions. The wide and deep information are explored for the object proposal windows extracted in each image. The window-level co-saliency scores are calculated by integrating the intra-image contrast, the intra-group consistency, and the inter-group separability via a principled Bayesian formulation and are then converted to the superpixel-level co-saliency maps through a foreground region agreement strategy. Comprehensive experiments on two existing and one newly established datasets have demonstrated the consistent performance gain of the proposed approach.

文章类型Article
关键词Co-saliency Detection Domain Adaptive Convolutional Neural Network Bayesian Framework
学科领域Computer Science, Artificial Intelligence
WOS标题词Science & Technology ; Technology
DOI10.1007/s11263-016-0907-4
收录类别SCI
关键词[WOS]VISUAL SALIENCY ; SEGMENTATION ; EXTRACTION ; MODEL ; DISCOVERY ; VIDEOS
语种英语
WOS研究方向Computer Science
项目资助者National Science Foundation of China(61522207 ; Doctorate Foundation ; Excellent Doctorate Foundation of Northwestern Polytechnical University ; 61473231)
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000382092900006
引用统计
被引频次:283[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/28413
专题光谱成像技术研究室
通讯作者Han, JW
作者单位1.Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China
2.Microsoft Res Asia, Beijing, Peoples R China
3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Dingwen,Han, Junwei,Li, Chao,et al. Detection of Co-salient Objects by Looking Deep and Wide[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2016,120(2):215-232.
APA Zhang, Dingwen,Han, Junwei,Li, Chao,Wang, Jingdong,Li, Xuelong,&Han, JW.(2016).Detection of Co-salient Objects by Looking Deep and Wide.INTERNATIONAL JOURNAL OF COMPUTER VISION,120(2),215-232.
MLA Zhang, Dingwen,et al."Detection of Co-salient Objects by Looking Deep and Wide".INTERNATIONAL JOURNAL OF COMPUTER VISION 120.2(2016):215-232.
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