Image Upsampling
Image Upsampling is a computational technique in image restoration that increases the spatial resolution of a low-resolution image by estimating and inserting high-frequency details through interpolation, learning-based prediction, or prior-driven reconstruction.
573
Publications
59.6K
Citations
2.4K
Authors
620
Institutions
Publications per year
2017–2026
396
Parents
573
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
Wei‐Sheng Lai, Jia‐Bin Huang, Narendra Ahuja et al. · 2017 · 3K citations
Understanding Convolution for Semantic Segmentation
Panqu Wang, Pengfei Chen, Ye Yuan et al. · 2018 · 2K citations
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
Simon Jégou, Michal Drozdzal, David Vázquez et al. · 2017 · 1.7K citations
Deep Back-Projection Networks for Super-Resolution
Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita · 2018 · 1.6K citations
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620

Chinese Academy of Sciences
Beijing, China
15 h-index
51 publications
2.5K citations
Tsinghua University
Beijing, China
14 h-index
46 publications
14.6K citations

Shanghai Jiao Tong University
Shanghai, China
14 h-index
52 publications
2.4K citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
13 h-index
39 publications
15.4K citations

Sun Yat-sen University
Guangzhou, China
13 h-index
33 publications
980 citations
ETH Zurich
Zurich, Switzerland
12 h-index
42 publications
19.6K citations

Zhejiang University
Hangzhou, China
12 h-index
39 publications
1.8K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
12 h-index
34 publications
12.1K citations
1–8 of 620
38 publications · 3.2K citations
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Repository · 49 publications · 2.1K citations
26
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18 publications · 1.8K citations
17
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19 publications · 1K citations
16
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TOG · 15 publications · 3.4K citations
15
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