Style Transfer
Style Transfer is a computational method that synthesizes the visual or textual characteristics of a source style onto target content while preserving its underlying structure, distinguishing it from other rendering or generation techniques by its focus on aesthetic or stylistic adaptation.
841
Publications
86K
Citations
2.8K
Authors
682
Institutions
Publications per year
2017–2026
790
841
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola et al. · 2017 · 21.9K citations · Full text
Generative Adversarial Networks: An Overview
Antonia Creswell, Tom White, Vincent Dumoulin et al. · IEEE Signal Processing Magazine · 2018 · 4.4K citations · Full text
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola et al. · arXiv (Cornell University) · 2017 · 2.3K citations · Full text
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682

Peking University
Beijing, China
24 h-index
107 publications
9.1K citations
Adobe Systems (United States)
San Jose, United States
24 h-index
63 publications
8.6K citations
Tsinghua University
Beijing, China
22 h-index
87 publications
5K citations

Zhejiang University
Hangzhou, China
21 h-index
119 publications
5.8K citations

Chinese Academy of Sciences
Beijing, China
20 h-index
67 publications
5.7K citations
University of Chinese Academy of Sciences
Beijing, China
18 h-index
54 publications
4K citations
Google (United States)
Mountain View, United States
16 h-index
56 publications
9.3K citations
Tencent (China)
Shenzhen, China
15 h-index
38 publications
3.7K citations
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Repository · 160 publications · 10.4K citations
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TOG · 24 publications · 2.5K citations
22
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20 publications · 1.4K citations
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Conference · 24 publications · 1.6K citations
20
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15 publications · 936 citations
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