中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Augmented Adversarial Training for Cross-Modal Retrieval

文献类型：期刊论文

作者Wu, Yiling2,3; Wang, Shuhui2; Song, Guoli4; Huang, Qingming1,2,5
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2021
卷号23页码:559-571
关键词Cross-modal retrieval data alignment adversa-rial training
ISSN号1520-9210
DOI10.1109/TMM.2020.2985540
英文摘要Cross-modal retrieval has received considerable attention in recent years. The core of cross-modal retrieval is to find a representation space to align data from different modalities according to their semantics. In this paper, we propose a cross-modal retrieval method that aligns data from different modalities by transferring one source modality to another target modality with augmented adversarial training. To preserve the semantic meaning in the modality transfer process, we employ the idea of conditional GANs and augment it. The key idea is to incorporate semantic information from the label space into the adversarial training process by sampling more semantic relevant and irrelevant source-target sample pairs. The augmented sample pairs improve the alignment from two aspects. First, relevant source-target sample pairs provide more training samples, leading to a better guidance of the alignment of fake targets and true paired targets. Second, relevant and irrelevant source-target sample pairs teach the discriminator to better distinguish true relevant pairs from fake relevant pairs, which guides the generator to better transfer from the source modality to the target modality. Extensive experiments compared with state-of-the-art methods show the promising power of our approach.
资助项目National Key R&D Program of China[2018AAA0102003] ; National Natural Science Foundation of China[61672497] ; National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[61836002] ; National Natural Science Foundation of China[61931008] ; National Natural Science Foundation of China[U1636214] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS013] ; China Postdoctoral Science Foundation[119103S291]
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:000613560200004
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/16251]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Wang, Shuhui
作者单位1.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 101408, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
3.Huawei Cloud & AI, Shenzhen 518129, Peoples R China
4.Peng Cheng Lab, Res Ctr Artificial Intelligence, Shenzhen 518066, Peoples R China
5.Peng Cheng Lab, Shenzhen 518066, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Yiling,Wang, Shuhui,Song, Guoli,et al. Augmented Adversarial Training for Cross-Modal Retrieval[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2021,23:559-571.
APA Wu, Yiling,Wang, Shuhui,Song, Guoli,&Huang, Qingming.(2021).Augmented Adversarial Training for Cross-Modal Retrieval.IEEE TRANSACTIONS ON MULTIMEDIA,23,559-571.
MLA Wu, Yiling,et al."Augmented Adversarial Training for Cross-Modal Retrieval".IEEE TRANSACTIONS ON MULTIMEDIA 23(2021):559-571.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。