The DOI matches its Crossref record; 261 of the 287 references it cites were found in a registry or an index.
Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications
Open accessAbstract
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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“It is becoming increasingly simple to use pretrained GAN to instantly replace one person's face in an image or video with the face of another person (Liu etal. 2021b).”
From Deepfake video detection: challenges and opportunities (2024) · cites this paper as Liu et al. 2021b
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Sorted by citations
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
Niemeyer, M., & Geiger, A. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01129 · Cited by 777
Deep Learning for Deepfakes Creation and Detection: A Survey
Nguyen, T. T., Nguyen, Q. V. H., Nguyen, D. T., Nguyen, D. T., Huynh-The, T., Nahavandi, S., Nguyen, T. T., Pham, Q.-V., & Nguyen, C. M. (2019) · arXiv · doi:10.48550/arxiv.1909.11573 · Cited by 464
Deep learning for deepfakes creation and detection: A survey
Nguyen, T. T., Nguyen, Q. V. H., Nguyen, D. T., Nguyen, D. T., Huynh-The, T., Nahavandi, S., Nguyen, T. T., Pham, Q.-V., & Nguyen, C. M. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103525 · Cited by 464
“nt common underlying mechanism for deepfake creation is deep learning models such as autoencoders and generative adversarial networks, which have been applied widely in the computer vision domain [2]–[4]. These models are used to examine facial expressions and movements of a person and synthesize facial images of anot…”
BackgroundOne-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing
Wang, T.-C., Mallya, A., & Liu, M.-Y. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00991 · Cited by 496
Self-citationPaint by Example: Exemplar-based Image Editing with Diffusion Models
Yang, B., Gu, S., Zhang, B., Zhang, T., Chen, X., Sun, X., Chen, D., & Wen, F. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01763 · Cited by 459
Metadata
- Authors
- Liu, M.-Y., Huang, X., Yu, J., Wang, T.-C., & Mallya, A.
- Affiliations
- Nvidia (United States) (US)
- Google (United States) (US)
- Venue
- Proceedings of the IEEE
- Published
- 2021-05
- Volume
- 109
- Issue
- 5
- Pages
- 839-862
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- 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
- 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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