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Task-Adaptive Attention for Image Captioning

文献类型：期刊论文

作者Yan, Chenggang1,2; Hao, Yiming1; Li, Liang3; Yin, Jian1; Liu, Anan4; Mao, Zhendong5; Chen, Zhenyu6,7; Gao, Xingyu8
刊名IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
出版日期2022
卷号32期号:1页码:43-51
ISSN号1051-8215
关键词Task analysis Visualization Feature extraction Decoding Computational modeling Adaptation models Feeds Image captioning attention mechanism transformer
DOI10.1109/TCSVT.2021.3067449
英文摘要Attention mechanisms are now widely used in image captioning models. However, most attention models only focus on visual features. When generating syntax related words, little visual information is needed. In this case, these attention models could mislead the word generation. In this paper, we propose Task-Adaptive Attention module for image captioning, which can alleviate this misleading problem and learn implicit non-visual clues which can be helpful for the generation of non-visual words. We further introduce a diversity regularization to enhance the expression ability of the Task-Adaptive Attention module. Extensive experiments on the MSCOCO captioning dataset demonstrate that by plugging our Task-Adaptive Attention module into a vanilla Transformer-based image captioning model, performance improvement can be achieved.
资助项目National Key Research and Development Program of China[2020YFB1406604] ; National Natural Science Foundation of China[61771457] ; National Natural Science Foundation of China[61732007] ; National Natural Science Foundation of China[61931008] ; National Natural Science Foundation of China[61672497] ; National Natural Science Foundation of China[61971268] ; National Natural Science Foundation of China[61772494] ; National Natural Science Foundation of China[62022083]
WOS研究方向Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000742183600008
源URL[http://119.78.100.204/handle/2XEOYT63/18266]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Liang
作者单位1.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China
2.Hangzhou Dianzi Univ, Dept Automat, Hangzhou 310018, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
4.Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
5.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230052, Peoples R China
6.State Grid Corp China, Big Data Ctr, Beijing 100031, Peoples R China
7.China Elect Power Res Inst, Beijing 100192, Peoples R China
8.Chinese Acad Sci, Inst Microelect, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Yan, Chenggang,Hao, Yiming,Li, Liang,et al. Task-Adaptive Attention for Image Captioning[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2022,32(1):43-51.
APA Yan, Chenggang.,Hao, Yiming.,Li, Liang.,Yin, Jian.,Liu, Anan.,...&Gao, Xingyu.(2022).Task-Adaptive Attention for Image Captioning.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,32(1),43-51.
MLA Yan, Chenggang,et al."Task-Adaptive Attention for Image Captioning".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 32.1(2022):43-51.

入库方式： OAI收割

来源：计算技术研究所

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