Constructing multilayer locality-constrained matrix regression framework for noise robust face super-resolution-Reference-Cited by-同舟云学术

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Constructing multilayer locality-constrained matrix regression framework for noise robust face super-resolution

Published:2021-02 Issue: Volume:110 Page:107539
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Gao Guangwei^ORCID,Yu Yi^ORCID,Xie Jin,Yang Jian,Yang Meng,Zhang Jian

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Six Talent Peaks Project in Jiangsu Province

Natural Science Foundation of Jiangsu Province

Soochow University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference40 articles.

1. Super-resolution person re-identification with semi-coupled low-rank discriminant dictionary learning;Jing;IEEE Trans. Image Process.,2017

2. Multi-resolution dictionary learning for face recognition;Luo;Pattern Recognit.,2019

3. Joint learning sparsifying linear transformation for low-resolution image synthesis and recognition;Wei;Pattern Recognit.,2017

4. Learning low-level vision;Freeman;Int. J. Comput. Vis.,2000

5. Global consistency, local sparsity and pixel correlation: a unified framework for face hallucination;Shi;Pattern Recognit.,2014

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