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Context propagation embedding network for weakly supervised semantic segmentation

文献类型：期刊论文

作者Xu, Yajun2; Mao, Zhendong3; Chen, Zhineng1; Wen, Xin2; Li, Yangyang4
刊名MULTIMEDIA TOOLS AND APPLICATIONS
出版日期2020-03-30
页码18
关键词Weakly supervised Semantic segmentation Context propagation High-quality visual cues
ISSN号1380-7501
DOI10.1007/s11042-020-08787-9
通讯作者Mao, Zhendong(maozhendong2008@gmail.com)
英文摘要Weakly-supervised semantic segmentation with image-level labels has much significance as it facilitates related practical applications under lightweight manual annotations. Recent researches first infer the visual cues, referred as discriminative regions corresponding to each object category on images using deep convolutional classification networks. Then they expand visual cues to generate initial segmentation masks. Despite the remarkable progress, the segmentation performance still remains unsatisfactory due to the absence of complete visual cues. Using these low-quality visual cues as prior will have the limitation on improving segmentation performance. To overcome this problem, we propose a novel context propagation embedding network, i.e., the CPENet to generate high-quality visual cues, which focuses on learning semantic relationship between each region and its surrounding neighbors and selectively propagates discriminative information to non-discriminative, object related regions. Our methods can provide reliable initial segmentation masks for training subsequent segmentation network to generate final segmentation results. In addition, we refined convolutional block attention module (CBAM) [30] to hierarchically extract more category-aware features by capturing global context related information and further promote the propagation process. Experiments on benchmark demonstrate that our proposed method obtains superior performance over the state-of-the-arts.
资助项目National Natural Science Foundation of China
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000522592200005
出版者SPRINGER
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/38758]  
专题数字内容技术与服务研究中心_远程智能医疗
通讯作者Mao, Zhendong
作者单位1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Informat Engn, Sch Cyber Secur, Beijing, Peoples R China
3.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei, Peoples R China
4.China Acad Elect & Informat Technol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Yajun,Mao, Zhendong,Chen, Zhineng,et al. Context propagation embedding network for weakly supervised semantic segmentation[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2020:18.
APA Xu, Yajun,Mao, Zhendong,Chen, Zhineng,Wen, Xin,&Li, Yangyang.(2020).Context propagation embedding network for weakly supervised semantic segmentation.MULTIMEDIA TOOLS AND APPLICATIONS,18.
MLA Xu, Yajun,et al."Context propagation embedding network for weakly supervised semantic segmentation".MULTIMEDIA TOOLS AND APPLICATIONS (2020):18.

入库方式： OAI收割

来源：自动化研究所

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