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Image quality assessment (IQA) forms a natural and often straightforward undertaking for humans, yet effective automation of the task remains highly challenging.
The proof and measurement of association between two things
C Spearman · 1904
Earlier work this paper cites.
A new measure of rank correlation
Maurice G Kendall · 1938
Earlier work this paper cites.
Rank analysis of incomplete block designs: I. the method of paired comparisons
Ralph Allan Bradley and Milton E Terry · 1952
Earlier work this paper cites.
Digital images and human vision
Andrew B Watson and Cynthia H Null · 1997
Earlier work this paper cites.
Live image quality assessment database
Hamid R Sheikh, Zhou Wang, Lawrence Cormack, and Alan C Bovik · 2003
Earlier work this paper cites.
Multiscale structural similarity for image quality assessment
Zhou Wang, Eero P Simoncelli, and Alan C Bovik · 2003
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Image information and visual quality
Hamid R Sheikh and Alan C Bovik · 2006
Earlier work this paper cites.
A statistical evaluation of recent full reference image quality assessment algorithms
Hamid R Sheikh, Muhammad F Sabir, and Alan C Bovik · 2006
Earlier work this paper cites.
Modern image quality assessment , volume 2
Zhou Wang and Alan C Bovik · 2006
Earlier work this paper cites.
Learning to rank: from pairwise approach to listwise approach
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li · 2007
Earlier work this paper cites.
Introduction to Information Retrieval
Christopher D Manning and Prabhakar Raghavan · 2008
Earlier work this paper cites.
Most apparent distortion: full-reference image quality assessment and the role of strategy
Eric Cooper Larson and Damon Michael Chandler · 2010
Earlier work this paper cites.
A general approximation framework for direct optimization of information retrieval measures
Tao Qin, Tie-Yan Liu, and Hang Li · 2010
Earlier work this paper cites.
On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
Earlier work this paper cites.
Learning to rank for information retrieval
Tie-Yan Liu · 2011
Earlier work this paper cites.
Fsim: A feature similarity index for image quality assessment
Lin Zhang, Lei Zhang, Xuanqin Mou, and David Zhang · 2011
Earlier work this paper cites.
Ava: A large-scale database for aesthetic visual analysis
Naila Murray, Luca Marchesotti, and Florent Perronnin · 2012
Earlier work this paper cites.
A no-reference metric for evaluating the quality of motion deblurring
Yiming Liu, Jue Wang, Sunghyun Cho, Adam Finkelstein, and Szymon Rusinkiewicz · 2013
Earlier work this paper cites.
Color image database tid2013: Peculiarities and preliminary results
Nikolay Ponomarenko, Oleg Ieremeiev, Vladimir Lukin, Karen Egiazarian, Lina Jin, Jaakko Astola, Benoit Vozel, Kacem Chehdi, Marco Carli, Federica Battisti, et al · 2013
Earlier work this paper cites.
Gradient magnitude similarity deviation: A highly efficient perceptual image quality index
Wufeng Xue, Lei Zhang, Xuanqin Mou, and Alan C Bovik · 2013
Earlier work this paper cites.
Learning to rank for information retrieval and natural language processing
Hang Li · 2014
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Quality of experience: advanced concepts, applications and methods
Sebastian Möller and Alexander Raake · 2014
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VSI: A visual saliency-induced index for perceptual image quality assessment
Lin Zhang, Ying Shen, and Hongyu Li · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Image database tid2013: Peculiarities, results and perspectives
Nikolay Ponomarenko, Lina Jin, Oleg Ieremeiev, Vladimir Lukin, Karen Egiazarian, Jaakko Astola, Benoit Vozel, Kacem Chehdi, Marco Carli, Federica Battisti, and Kuo C.-C. Jay · 2015
Cited alongside, same era.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Pieapp: Perceptual image-error assessment through pairwise preference
Ekta Prashnani, Hong Cai, Yasamin Mostofi, and Pradeep Sen · 2018
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Semantic-aware blind image quality assessment
Ernestasia Siahaan, Alan Hanjalic, and Judith A Redi · 2018
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A benchmark of dibr synthesized view quality assessment metrics on a new database for immersive media applications
Shishun Tian, Lu Zhang, Luce Morin, and Olivier Déforges · 2018
Later among the works it cites.
Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
Later among the works it cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Later among the works it cites.
Sodeep: a sorting deep net to learn ranking loss surrogates
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Very deep convolutional networks for large-scale image recognition
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TensorFlow: a system for Large-Scale machine learning
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Cited alongside, same era.
Geodesics of learned representations
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Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
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Perceptual image quality assessment using a normalized laplacian pyramid
Valero Laparra, Johannes Ballé, Alexander Berardino, and Eero P Simoncelli · 2016
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Does visual quality depend on semantics? a study on the relationship between impairment annoyance and image semantics at early attentive stages
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Martin Engilberge, Louis Chevallier, Patrick Pérez, and Matthieu Cord · 2019
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Kadid-10k: A large-scale artificially distorted iqa database
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Quality evaluation of image dehazing methods using synthetic hazy images
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Pytorch: An imperative style, high-performance deep learning library
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An unsupervised information-theoretic perceptual quality metric
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Fast differentiable sorting and ranking
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Smooth-ap: Smoothing the path towards large-scale image retrieval
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Pipal: a large-scale image quality assessment dataset for perceptual image restoration
Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy S Ren, and Chao Dong · 2020
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Norm-in-norm loss with faster convergence and better performance for image quality assessment
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Perceptual image quality assessment with transformers
Manri Cheon, Sung-Jun Yoon, Byungyeon Kang, and Junwoo Lee · 2021
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Image quality assessment: Unifying structure and texture similarity
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P Simoncelli · 2021
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NTIRE 2021 challenge on perceptual image quality assessment
Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S Ren, Yu Qiao, Shuhang Gu, and Radu Timofte · 2021
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Unified quality assessment of in-the-wild videos with mixed datasets training
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Uncertainty-aware blind image quality assessment in the laboratory and wild
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https://www.mindspore.cn/
MindSpore · 2022
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