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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 3
649-658

Review of research on improvement and application of generative adversarial networks

Zhang Bin1
Zhou Yuechuan2
Zhang Min3
Li Jia3
Zhang Jianxun2
Guo Zhigang4
1. Mianyang Teachers' College, Mianyang Sichuan 621000, China
2. College of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China
3. Chongqing CEPREI Industrial Technology Institute Co. , Ltd. , Chongqing 401332, China
4. Unit 32086 of PLA, Chengdu 610000, China
DOI: 10.19734/j.issn.1001-3695.2022.08.0410

Abstract

Generative adversarial network(GAN), as an emerging generative model, has been gradually developed and applied in the fields of image generation, 3D reconstruction, cross-modal conversion, etc. It effectively solves the problem of inefficiency of conventional convolutional neural networks in image-generating tasks and fills the shortage of deep learning in the field of image generation. In order to help subsequent researchers quickly and comprehensively understand GAN, this paper sorted out the improved model of GAN based on the literature in recent years. It firstly introduced the basic principles of GAN from two perspectives of network structure and objective function, then elaborated and summarized various derivative models of GAN from two major perspectives of improvement and application types. Secondly it summarized and analyzed the quality and diversity of generated images from the perspectives of subjective qualitative, objective quantitative and task-specific evaluation. Finally, this paper discussed some core issues and latest research progress of GAN series models in recent years and analyzed the future development trend.

Foundation Support

国家自然科学基金资助项目(61971078)
2021年工业和信息化部高质量发展专项资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.08.0410
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 3
Section: Survey
Pages: 649-658
Serial Number: 1001-3695(2023)03-002-0649-10

Publish History

[2022-10-28] Accepted Paper
[2023-03-05] Printed Article

Cite This Article

张彬, 周粤川, 张敏, 等. 生成对抗网络改进角度与应用研究综述 [J]. 计算机应用研究, 2023, 40 (3): 649-658. (Zhang Bin, Zhou Yuechuan, Zhang Min, et al. Review of research on improvement and application of generative adversarial networks [J]. Application Research of Computers, 2023, 40 (3): 649-658. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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