A hybrid non-local enhanced network for lightweight single image super-resolution-Reference-Cited by-同舟云学术

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A hybrid non-local enhanced network for lightweight single image super-resolution

Published:2023-08-15 Issue: Volume: Page:
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

He Zheng,Yang Haoran,Chen Lihui,Jeon Gwanggil,Liu Yiguang,Yang Xiaomin

Funder

Sichuan Province Science and Technology Support Program

Sichuan University

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-023-11913-0.pdf

Reference48 articles.

1. Agustsson E, Timofte R (2017) Ntire 2017 challenge on single image super-resolution: dataset and study. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp 1122–1131

2. Ahn N, Kang B, Sohn KA (2018) Fast, accurate, and lightweight super-resolution with cascading residual network. In: Proceedings of the European Conference on Computer Vision (ECCV), pp 252–268

3. Bevilacqua M, Roumy A, Guillemot C, et al (2012) Low-complexity single-image super-resolution based on nonnegative neighbor embedding. In: British Machine Vision Conference (BMVC)

4. Cao Y, Xu J, Lin S, et al (2019) Gcnet: non-local networks meet squeeze-excitation networks and beyond. In: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), pp 1971–1980

5. Chi L, Yuan Z, Mu Y, et al (2020) Non-local neural networks with grouped bilinear attentional transforms. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 11,804–11,813

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