Inpainting
Inpainting is a computational image synthesis task that belongs to the broader category of image restoration methods, specifically distinguished by its objective of plausibly reconstructing missing or occluded regions within an image based on learned semantic and structural priors from surrounding context.
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Marcelo Bertalmı́o, Guillermo Sapiro, V. Caselles et al. · 2000 · 3.6K citations · Full text
Generative Image Inpainting with Contextual Attention
Jiahui Yu, Zhe Lin, Xiaohui Shen et al. · 2018 · 2.5K citations
Learning Deep CNN Denoiser Prior for Image Restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu et al. · 2017 · 2.1K citations · Full text
Pre-Trained Image Processing Transformer
Hanting Chen, Yunhe Wang, Tianyu Guo et al. · 2021 · 2K citations
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Chinese Academy of Sciences
Beijing, China
24 h-index
97 publications
7.4K citations
Nanyang Technological University
Singapore, Singapore
24 h-index
61 publications
5.5K citations

Centre National de la Recherche Scientifique
Paris, France
23 h-index
94 publications
4.3K citations
Adobe Systems (United States)
San Jose, United States
23 h-index
62 publications
20.4K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
22 h-index
69 publications
8.5K citations
University of Science and Technology of China
Hefei, China
21 h-index
83 publications
11.3K citations
University of California, Los Angeles
Los Angeles, United States
21 h-index
46 publications
9K citations
University of Chinese Academy of Sciences
Beijing, China
21 h-index
68 publications
3.7K citations
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80 publications · 9.1K citations
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Repository · 150 publications · 8.6K citations
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30 publications · 1.9K citations
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TPAMI · 27 publications · 3.5K citations
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SIIMS · 25 publications · 1.5K citations
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