Image super-resolution with channel-attention-embedded Transformer-Reference-Cited by-同舟云学术

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Image super-resolution with channel-attention-embedded Transformer

Published:2023 Issue:12 Volume:28 Page:3744-3757
ISSN:1006-8961
Container-title:Journal of Image and Graphics
language:en
Short-container-title:

Author:

Wei Xiong, ,Chengyi Xiong,Zhirong Gao,Wenqi Chen,Ruihua Zheng,Jinwen Tian

Publisher

Aerospace Information Research Institute, Chinese Academy of Sciences

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference35 articles.

1. Agustsson E and Timofte R.2017.NTIRE 2017 challenge on single image super-resolution:dataset and study//Proceedings of 2017IEEE Conference on Computer Vision and Pattern Recognition Workshops.Honolulu,USA:IEEE:1122-1131[DOI:10.1109/CVPRW.2017.150]

2. Ahn N,Kang B and Sohn K A.2018.Fast,accurate,and lightweight super-resolution with cascading residual network//Proceedings of the 15th European Conference on Computer Vision.Munich,Germany:Springer:256-272[DOI:10.1007/978-3-030-01249-6_16]

3. Bevilacqua M,Roumy A,Guillemot C and Morel M L A.2012.Lowcomplexity single-image super-resolution based on nonnegative neighbor embedding//Proceedings of the 23rd British Machine Vision Conference.Surrey,UK:BMVA Press:1-12[DOI:10.5244/c.26.135]

4. Chen H T,Wang Y H,Guo T Y,Xu C,Deng Y P,Liu Z H,Ma S W,Xu C J,Xu C and Gao W.2021.Pre-trained image processing Transformer//Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR).Nashville,USA:IEEE:12294-12305[DOI:10.1109/CVPR46437.2021.01212]

5. Dong C,Loy C C,He K M and Tang X O.2014.Learning a deep convolutional network for image super-resolution//Proceedings of the 13th European Conference on Computer Vision.Zurich,Switzerland:Springer:184-199[DOI:10.1007/978-3-319-10593-2_13]

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