Cited by 237Generative Adversarial Networks and Image SynthesisDigital Media Forensic DetectionAdvanced Image Processing Techniques

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Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications

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Liu, Ming-Yu, Huang, Xun, Yu, Jiahui, Wang, Ting-Chun, Mallya, Arun·2021·Proceedings of the IEEE

DOI 10.1109/jproc.2021.3049196

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Abstract

The generative adversarial network (GAN) framework has emerged as a powerful tool for various image and video synthesis tasks, allowing the synthesis of visual content in an unconditional or input-conditional manner. It has enabled the generation of high-resolution photorealistic images and videos, a task that was challenging or impossible with prior methods. It has also led to the creation of many new applications in content creation. In this article, we provide an overview of GANs with a special focus on algorithms and applications for visual synthesis. We cover several important techniques to stabilize GAN training, which has a reputation for being notoriously difficult. We also discuss its applications to image translation, image processing, video synthesis, and neural rendering.

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Authors: Liu, M.-Y., Huang, X., Yu, J., Wang, T.-C., & Mallya, A.
Affiliations: Nvidia (United States) (US)
Google (United States) (US)
ORCID: Liu, Ming-Yu
Yu, Jiahui
Wang, Ting-Chun
Mallya, Arun
Venue: Proceedings of the IEEE
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2021-05
Volume: 109
Issue: 5
Pages: 839-862
ISSN: 0018-9219 (ISSN-L)
1558-2256
DOI: 10.1109/jproc.2021.3049196
OpenAlex: W3126434301
Cited by: 236
References: 287
Citations by year: 2026: 16 · 2025: 51 · 2024: 63 · 2023: 39 · 2022: 37 · 2021: 27
FWCI: 14.93
Type: journal article
Language: en
Open access: green
arxiv.org
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
Locations: Proceedings of the IEEE (publishedVersion)
arXiv (Cornell University) (submittedVersion)
arXiv (Cornell University)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image Processing Techniques
Keywords: generative adversarial networks, image generation, video generation, GAN training stability, image-to-image translation, image processing, neural rendering, realistic image synthesis, conditional generation

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Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications

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