Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)

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Applications of Generative Adversarial Network Technologies for Image Generation

Authors
Zhixuan He1, *
1School of Mathematics and Statistics, Shandong University, Shandong, 264209, China
*Corresponding author. Email: 202200820051@mail.sdu.edu.cn
Corresponding Author
Zhixuan He
Available Online 23 September 2024.
DOI
10.2991/978-94-6463-512-6_39How to use a DOI?
Keywords
Generative Adversarial Network; Image Generation; Deep Learning
Abstract

Image generation is crucial in the digital age, revolutionizing the way that people perceive and interact with visual content. It is a cornerstone for various industries, from advertising and marketing to film production and gaming. By enabling the creation of images, it fuels creativity, enriches storytelling, and enhances user engagement. The content of this article is to summarize and analyses the advancement generative adversarial network (GAN)-based image generation. GAN has produced impressive achievements and serves a variety of purposes in the realm of images. It is a deep learning model, which consists of a generator and a discriminator, and the adversarial methods are used in training this model. In this paper, the basic theory of GAN is described, and then the various applications of GAN in the image field are introduced in detail, including the applications of image generation, image modification, image style transfer and image restoration. Finally, some existing problems of the model are discussed, and its development direction and trend are forecasted.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
Series
Advances in Intelligent Systems Research
Publication Date
23 September 2024
ISBN
978-94-6463-512-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-512-6_39How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zhixuan He
PY  - 2024
DA  - 2024/09/23
TI  - Applications of Generative Adversarial Network Technologies for Image Generation
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
PB  - Atlantis Press
SP  - 363
EP  - 372
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-512-6_39
DO  - 10.2991/978-94-6463-512-6_39
ID  - He2024
ER  -