Title
From Distortion Manifold to Perceptual Quality: a Data Efficient Blind Image Quality Assessment Approach
Abstract
•We explore to improve generalize ability of blind IQA models with limited training data•We propose to explicitly learn a distortion manifold•A novel model proposed to extract both low level distortion patterns and high level semantic information•An effective training framework including a masked labeling strategy and a gradual weighting curriculum
Year
DOI
Venue
2023
10.1016/j.patcog.2022.109047
Pattern Recognition
Keywords
DocType
Volume
Image quality assessment,No-Reference,Generalizability,Distortion manifold
Journal
133
ISSN
Citations 
PageRank 
0031-3203
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Shaolin Su101.35
Yan, Q.2707.01
Yu Zhu38812.65
Jinqiu Sun4338.27
Yanning Zhang51613176.32