Image Super-Resolution via Efficient Transformer Embedding Frequency Decomposition With Restart-Reference-Cited by-同舟云学术

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Image Super-Resolution via Efficient Transformer Embedding Frequency Decomposition With Restart

Published:2024 Issue: Volume:33 Page:4670-4685
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Zuo Yifan¹^ORCID,Yao Wenhao¹,Hu Yuqi¹,Fang Yuming¹^ORCID,Liu Wei²^ORCID,Peng Yuxin³^ORCID

Affiliation:

1. School of Information Management, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China

2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

3. Wangxuan Institute of Computer Technology, Peking University, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi Province

Pujiang Program

Double Thousand Plan of Jiangxi Province

Jiangxi Provincial Key Laboratory of Multimedia Intelligent Processing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/83/10346232/10643469.pdf?arnumber=10643469

Reference66 articles.

1. Image Super-Resolution Using Deep Convolutional Networks

2. Enhanced Deep Residual Networks for Single Image Super-Resolution

3. Residual Dense Network for Image Super-Resolution

4. Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution

5. A ConvNet for the 2020s

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