Journal of Frontiers of Computer Science and Technology ›› 2022, Vol. 16 ›› Issue (10): 2234-2248.DOI: 10.3778/j.issn.1673-9418.2112080

• Surveys and Frontiers • Previous Articles     Next Articles

Review of Image Captioning Methods Based on Encoding-Decoding Technology

GENG Yaogang, MEI Hongyan+(), ZHANG Xing, LI Xiaohui   

  1. School of Electronic and Information Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121000, China
  • Received:2021-12-20 Revised:2022-04-19 Online:2022-10-01 Published:2022-10-14
  • About author:GENG Yaogang, born in 1997, M.S. candidate.His research interests include natural language processing and image captioning.
    MEI Hongyan, born in 1978, Ph.D., associate professor, member of CCF. Her research interests include data mining, big data analysis and network services.
    ZHANG Xing, born in 1975, Ph.D., professor, member of CCF. His research interests include network architecture and protocol and information security.
    LI Xiaohui, born in 1978, Ph.D., associate professor. Her research interests include network security, privacy protection and cloud computing.
  • Supported by:
    National Natural Science Foundation for Youth of China(61802161);Scientific Research Project of Liaoning Provincial Department of Education(JZL202015404);Scientific Research Project of Liaoning Provincial Department of Education(LJKZ0625);General Project of Liaoning Provincial Department of Education(LJKZ0618)


耿耀港, 梅红岩+(), 张兴, 李晓会   

  1. 辽宁工业大学 电子与信息工程学院,辽宁 锦州 121000
  • 通讯作者: + E-mail:
  • 作者简介:耿耀港(1997—),男,山东济宁人,硕士研究生,主要研究方向为自然语言处理、图像标题生成。
  • 基金资助:


In recent years, image caption generation, as a multimodal task in the field of artificial intelligence, integrates the related research of computer vision and natural language processing, and can realize the modal conversion from image to text. It plays an important role in visual assistance and image understanding, and has attracted extensive attention from researchers. Firstly, this paper describes the task of image caption generation, and introduces three image caption generation methods: template-based method, retrieval-based method and encode-decode method. Their respective method ideas, representative research and advantages and disadvantages are also introduced. Secondly, from the model structure, the research progress of image understanding phase and caption generation phase, this paper expounds in detail the method based on encoding-decoding, and summarizes the research over years into the research of image understanding and caption generation. Image understanding research includes attention mechanism and semantic aspects. The research of caption generation is divided into traditional caption generation, dense caption generation and stylish caption generation. The performance, advantages and disadvantages of the model are summarized, and the datasets and evaluation index of the performance evaluation of the image captioning model are introduced. Finally, the challenges and difficulties in the field of image captioning are pointed out.

Key words: image caption generation, encode, decode, multimodal, attention mechanism



关键词: 图像标题生成, 编码, 解码, 多模态, 注意力机制

CLC Number: