Back-projection-based progressive growing generative adversarial network for single image super-resolution
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Since 2014, generative adversarial training algorithms have been widely used in unimodal applications such as scene generation, image-to-image translation, and image super-resolution.
“Since their development in 2014, generative adversarial training algorithms have been widely used in various unimodal applications such as scene generation [17], image-to-image translation [18], and image super-resolution [224, 225].”
From A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets (2022) · cites this paper as [225]
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Bayoudh, K., Knani, R., Hamdaoui, F., & Mtibaa, A. (2022) · The Visual Computer · doi:10.1007/s00371-021-02166-7 · Cited by 456 · see citing works
- Authors
- Ma, T., & Tian, W.
- Affiliations
- University of Electronic Science and Technology of China (CN)
- Corresponding author
- Tian, Wenhong
- Venue
- The Visual Computer
- Published
- 2020-04-30
- Volume
- 37
- Issue
- 5
- Pages
- 925-938
- ISSN
- 0178-2789 (ISSN-L)
- 1432-2315
- OpenAlex
- W3023669178
- Cited by
- 16
- References
- 53
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 2 · 2020: 3
- FWCI
- 1.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Visual Computer (publishedVersion)
- Funders
- Natural Science Foundation of China (2018AAA003203)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image Processing Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Keywords
- single image super-resolution, generative adversarial networks, feedback mechanisms, multi-scale feature learning, training stability
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