GLA: Global-Local Attention for Image Description
文献类型：期刊论文
| 作者 | Li, Linghui1,3; Tang, Sheng1,3; Zhang, Yongdong1,3; Deng, Lixi1,3; Tian, Qi2 |
| 刊名 | IEEE TRANSACTIONS ON MULTIMEDIA
 |
| 出版日期 | 2018-03-01 |
| 卷号 | 20期号:3页码:726-737 |
| 关键词 | Convolutional neural network recurrent neural network image description natural language processing |
| ISSN号 | 1520-9210 |
| DOI | 10.1109/TMM.2017.2751140 |
| 英文摘要 | In recent years, the task of automatically generating image description has attracted a lot of attention in the field of artificial intelligence. Benefitting from the development of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), many approaches based on the CNN-RNN framework have been proposed to solve this task and achieved remarkable process. However, two problems remain to be tackled in which the most existing methods use only the image-level representation. One problem is object missing, in which some important objects may he missing when generating the image description and the other is misprediction, when one object may be recognized in a wrong category. In this paper, to address these two problems, we propose a new method called global-local attention (GLA) for generating image description. The proposed GLA model utilizes an attention mechanism to integrate object-level features with image-level feature. Through this manner, our model can selectively pay attention to objects and context information concurrently. Therefore, our proposed GLA method can generate more relevant image description sentences and achieve the state-of-the-art performance on the well-known Microsoft COCO caption dataset with several popular evaluation metrics-CIDEr, METEOR, ROUGE-L and BLEU-1, 2,3, 4. |
| 资助项目 | National Key Research and Development Program of China[2017YFB1002202] ; Beijing Natural Science Foundation[4152050] ; Beijing Advanced Innovation Center for Imaging Technology[BAICIT-2016009] ; ARO[W911NF-15-1-0290] ; National Natural Science Foundation of China[61525206] ; National Natural Science Foundation of China[61572472] ; National Natural Science Foundation of China[61429201] |
| WOS研究方向 | Computer Science ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000425397500017 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5630]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Tang, Sheng |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Linghui,Tang, Sheng,Zhang, Yongdong,et al. GLA: Global-Local Attention for Image Description[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(3):726-737. |
| APA | Li, Linghui,Tang, Sheng,Zhang, Yongdong,Deng, Lixi,&Tian, Qi.(2018).GLA: Global-Local Attention for Image Description.IEEE TRANSACTIONS ON MULTIMEDIA,20(3),726-737. |
| MLA | Li, Linghui,et al."GLA: Global-Local Attention for Image Description".IEEE TRANSACTIONS ON MULTIMEDIA 20.3(2018):726-737. |
入库方式： OAI收割
来源：计算技术研究所
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