Meta-Learning-Based Degradation Representation for Blind Super-Resolution-Reference-Cited by-同舟云学术

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Meta-Learning-Based Degradation Representation for Blind Super-Resolution

Published:2023 Issue: Volume:32 Page:3383-3396
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Xia Bin¹^ORCID,Tian Yapeng²^ORCID,Zhang Yulun³^ORCID,Hang Yucheng¹,Yang Wenming¹^ORCID,Liao Qingmin¹^ORCID

Affiliation:

1. Department of Electronic Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA

3. Computer Vision Laboratory, ETH Zürich, Zürich, Switzerland

Funder

Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Special Foundation for the Development of Strategic Emerging Industries of Shenzhen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10149119.pdf?arnumber=10149119

Reference64 articles.

1. Unfolding the alternating optimization for blind super resolution;luo;arXiv 2010 02631,2020

2. Tackling the Ill-Posedness of Super-Resolution through Adaptive Target Generation

3. Blind Super-Resolution With Iterative Kernel Correction

4. SwinIR: Image Restoration Using Swin Transformer

5. Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

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1. MFHOD: Multi-modal image fusion method based on the higher-order degradation model;Expert Systems with Applications;2024-09

2. Parallel Alternating Iterative Optimization for Cardiac Magnetic Resonance Image Blind Super-Resolution;IEEE Journal of Biomedical and Health Informatics;2024-09

3. Kernel adaptive memory network for blind video super-resolution;Expert Systems with Applications;2024-03

4. Adaptive Blind Super-Resolution Network for Spatial-Specific and Spatial-Agnostic Degradations;IEEE Transactions on Image Processing;2024

5. A Progressive Decoupled Network for Blind Image Super-Resolution;IEEE Access;2024

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