Unsupervised Semantic-Based Aggregation of Deep Convolutional Features | |
Xu, Jian1,2; Wang, Chunheng2; Qi, Chengzuo1,2; Shi, Cunzhao2; Xiao, Baihua2 | |
发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
ISSN | 1057-7149 |
2019-02-01 | |
卷号 | 28期号:2页码:601-611 |
摘要 | In this paper, we propose a simple but effective semantic-based aggregation (SBA) method. The proposed SBA utilizes the discriminative filters of deep convolutional layers as semantic detectors. Moreover, we propose the effective unsupervised strategy to select some semantic detectors to generate the "soft region proposals," which highlight certain discriminative pattern of objects and suppress the noise of background. The final global SBA representation could then be acquired by aggregating the regional representations weighted by the selected " soft region proposals" corresponding to various semantic content. Our unsupervised SBA is easy to generalize and achieves excellent performance on various tasks. We conduct comprehensive experiments and show that our unsupervised SBA outperforms the state-of-the-art unsupervised and supervised aggregation methods on image retrieval, place recognition, and cloud classification. |
关键词 | Unsupervised semantic-based aggregation semantic detectors |
DOI | 10.1109/TIP.2018.2867104 |
关键词[WOS] | IMAGE RETRIEVAL ; SCALE ; CLASSIFICATION ; RECOGNITION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[61601462] ; National Natural Science Foundation of China[61531019] ; National Natural Science Foundation of China[61531019] ; National Natural Science Foundation of China[61601462] ; National Natural Science Foundation of China[71621002] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000446255300006 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 图像视频处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/25733 |
专题 | 复杂系统管理与控制国家重点实验室_影像分析与机器视觉 |
通讯作者 | Wang, Chunheng |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xu, Jian,Wang, Chunheng,Qi, Chengzuo,et al. Unsupervised Semantic-Based Aggregation of Deep Convolutional Features[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2019,28(2):601-611. |
APA | Xu, Jian,Wang, Chunheng,Qi, Chengzuo,Shi, Cunzhao,&Xiao, Baihua.(2019).Unsupervised Semantic-Based Aggregation of Deep Convolutional Features.IEEE TRANSACTIONS ON IMAGE PROCESSING,28(2),601-611. |
MLA | Xu, Jian,et al."Unsupervised Semantic-Based Aggregation of Deep Convolutional Features".IEEE TRANSACTIONS ON IMAGE PROCESSING 28.2(2019):601-611. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
SBA.pdf(1963KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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