OPT OpenIR  > 光谱成像技术研究室
3G structure for image caption generation
Yuan, Aihong1,2; Li, Xuelong1; Lu, Xiaoqiang1
作者部门光谱成像技术研究室
2019-02-22
发表期刊Neurocomputing
ISSN9252312;18728286
卷号330页码:17-28
产权排序1
摘要

It is a big challenge of computer vision to make machine automatically describe the content of an image with a natural language sentence. Previous works have made great progress on this task, but they only use the global or local image feature, which may lose some important subtle or global information of an image. In this paper, we propose a model with 3-gated model which fuses the global and local image features together for the task of image caption generation. The model mainly has three gated structures. (1) Gate for the global image feature, which can adaptively decide when and how much the global image feature should be imported into the sentence generator. (2) The gated recurrent neural network (RNN) is used as the sentence generator. (3) The gated feedback method for stacking RNN is employed to increase the capability of nonlinearity fitting. More specially, the global and local image features are combined together in this paper, which makes full use of the image information. The global image feature is controlled by the first gate and the local image feature is selected by the attention mechanism. With the latter two gates, the relationship between image and text can be well explored, which improves the performance of the language part as well as the multi-modal embedding part. Experimental results show that our proposed method outperforms the state-of-the-art for image caption generation. ? 2018

DOI10.1016/j.neucom.2018.10.059
收录类别EI
语种英语
出版者Elsevier B.V.
EI入藏号20184506050720
引用统计
被引频次:24[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/31099
专题光谱成像技术研究室
通讯作者Lu, Xiaoqiang
作者单位1.Center for OPTical IMagery Analysis and Learning (OPTIMAL), Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; Shaanxi; 710119, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China
推荐引用方式
GB/T 7714
Yuan, Aihong,Li, Xuelong,Lu, Xiaoqiang. 3G structure for image caption generation[J]. Neurocomputing,2019,330:17-28.
APA Yuan, Aihong,Li, Xuelong,&Lu, Xiaoqiang.(2019).3G structure for image caption generation.Neurocomputing,330,17-28.
MLA Yuan, Aihong,et al."3G structure for image caption generation".Neurocomputing 330(2019):17-28.
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