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Structure Preserving Convolutional Attention for Image Captioning

文献类型：期刊论文

作者Lu, Shichen1,2,5; Hu, Ruimin1,2; Liu, Jing3; Guo, Longteng3; Zheng, Fei4
刊名APPLIED SCIENCES-BASEL
出版日期2019-07-02
卷号9期号:14页码:10
关键词image captioning attention spatial structure deep learning computer vision
DOI10.3390/app9142888
通讯作者Hu, Ruimin(hrm@whu.edu.cn)
英文摘要In the task of image captioning, learning the attentive image regions is necessary to adaptively and precisely focus on the object semantics relevant to each decoded word. In this paper, we propose a convolutional attention module that can preserve the spatial structure of the image by performing the convolution operation directly on the 2D feature maps. The proposed attention mechanism contains two components: convolutional spatial attention and cross-channel attention, aiming to determine the intended regions to describe the image along the spatial and channel dimensions, respectively. Both of the two attentions are calculated at each decoding step. In order to preserve the spatial structure, instead of operating on the vector representation of each image grid, the two attention components are both computed directly on the entire feature maps with convolution operations. Experiments on two large-scale datasets (MSCOCO and Flickr30K) demonstrate the outstanding performance of our proposed method.
资助项目National Nature Science Foundation of China[U1736206]
WOS研究方向Chemistry ; Materials Science ; Physics
语种英语
WOS记录号WOS:000479026900115
出版者MDPI
资助机构National Nature Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/27613]  
专题自动化研究所_模式识别国家重点实验室_图像与视频分析团队
通讯作者Hu, Ruimin
作者单位1.Wuhan Univ, Natl Engn Res Ctr Multimedia Software, Sch Comp, Wuhan 430072, Hubei, Peoples R China
2.Wuhan Univ, Hubei Key Lab Multimedia & Network Commun Engn, Wuhan 430072, Hubei, Peoples R China
3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
4.China Gen Technol Res Inst, Beijing 100190, Peoples R China
5.Wuhan Univ, Informat Dept, Dormitory 8,Room 617, Wuhan 430072, Hubei, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Shichen,Hu, Ruimin,Liu, Jing,et al. Structure Preserving Convolutional Attention for Image Captioning[J]. APPLIED SCIENCES-BASEL,2019,9(14):10.
APA Lu, Shichen,Hu, Ruimin,Liu, Jing,Guo, Longteng,&Zheng, Fei.(2019).Structure Preserving Convolutional Attention for Image Captioning.APPLIED SCIENCES-BASEL,9(14),10.
MLA Lu, Shichen,et al."Structure Preserving Convolutional Attention for Image Captioning".APPLIED SCIENCES-BASEL 9.14(2019):10.

入库方式： OAI收割

来源：自动化研究所

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