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Image Captioning by Asking Questions

文献类型：期刊论文

作者Yang, Xiaoshan; XU, Changsheng
刊名ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
出版日期2019-08-01
卷号15期号:2页码:19
关键词Image captioning visual question answering attention networks
ISSN号1551-6857
DOI10.1145/3313873
通讯作者Yang, Xiaoshan(xiaoshan.yang@nlpr.ia.ac.cn)
英文摘要Image captioning and visual question answering are typical tasks that connect computer vision and natural language processing. Both of them need to effectively represent the visual content using computer vision methods and smoothly process the text sentence using natural language processing skills. The key problem of these two tasks is to infer the target result based on the interactive understanding of the word sequence and the image. Though they practically use similar algorithms, they are studied independently in the past few years. In this article, we attempt to exploit the mutual correlation between these two tasks. We propose the first VQA-improved image-captioning method that transfers the knowledge learned from the VQA corpora to the image-captioning task. A VQA model is first pretrained on image-question-answer instances. Then, the pretrained VQA model is used to extract VQA-grounded semantic representations according to selected free-form open-ended visual question-answer pairs. The VQA-grounded features are complementary to the visual features, because they interpret images from a different perspective. We incorporate the VQA model into the image-captioning model by adaptively fusing the VQA-grounded feature and the attended visual feature. We show that such simple VQA-improved image-captioning (VQA-IIC) models perform better than conventional image-captioning methods on large-scale public datasets.
WOS关键词VIDEO
资助项目National Key Research and Development Program of China[2017YFB1002804] ; National Natural Science Foundation of China[61702511] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61620106003] ; National Natural Science Foundation of China[61432019] ; National Natural Science Foundation of China[61632007] ; National Natural Science Foundation of China[U1705262] ; National Natural Science Foundation of China[U1836220] ; Key Research Program of Frontier Sciences, CAS[QYZDJSSWJSC039] ; Research Program of National Laboratory of Pattern Recognition[Z-2018007] ; CCF-Tencent Open Fund
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000482001900008
出版者ASSOC COMPUTING MACHINERY
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; Research Program of National Laboratory of Pattern Recognition ; CCF-Tencent Open Fund
源URL[http://ir.ia.ac.cn/handle/173211/27571]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Yang, Xiaoshan
作者单位Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Xiaoshan,XU, Changsheng. Image Captioning by Asking Questions[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2019,15(2):19.
APA Yang, Xiaoshan,&XU, Changsheng.(2019).Image Captioning by Asking Questions.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,15(2),19.
MLA Yang, Xiaoshan,et al."Image Captioning by Asking Questions".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 15.2(2019):19.

入库方式： OAI收割

来源：自动化研究所

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