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Test your samples jointly: Pseudo-reference for image quality evaluation

Test your samples jointly: Pseudo-reference for image quality evaluation

7 April 2023
Marcelin Tworski
Stéphane Lathuilière
ArXivPDFHTML

Papers citing "Test your samples jointly: Pseudo-reference for image quality evaluation"

15 / 15 papers shown
Title
Image Quality Assessment using Contrastive Learning
Image Quality Assessment using Contrastive Learning
Pavan C. Madhusudana
Neil Birkbeck
Yilin Wang
Balu Adsumilli
A. Bovik
SSL
34
167
0
25 Oct 2021
Learning Conditional Knowledge Distillation for Degraded-Reference Image
  Quality Assessment
Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
Heliang Zheng
Huan Yang
Jianlong Fu
Zhengjun Zha
Jiebo Luo
51
42
0
18 Aug 2021
No-Reference Image Quality Assessment via Transformers, Relative
  Ranking, and Self-Consistency
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
S. Golestaneh
Saba Dadsetan
Kris Kitani
ViT
51
248
0
16 Aug 2021
MUSIQ: Multi-scale Image Quality Transformer
MUSIQ: Multi-scale Image Quality Transformer
Junjie Ke
Qifei Wang
Yilin Wang
P. Milanfar
Feng Yang
221
666
0
12 Aug 2021
A combined full-reference image quality assessment approach based on
  convolutional activation maps
A combined full-reference image quality assessment approach based on convolutional activation maps
D. Varga
48
7
0
19 Oct 2020
DR2S : Deep Regression with Region Selection for Camera Quality
  Evaluation
DR2S : Deep Regression with Region Selection for Camera Quality Evaluation
Marcelin Tworski
Stéphane Lathuilière
Salim Belkarfa
Attilio Fiandrotti
Marco Cagnazzo
3DH
27
4
0
21 Sep 2020
MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessment
MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessment
Hancheng Zhu
Leida Li
Jinjian Wu
W. Dong
Guangming Shi
82
280
0
11 Apr 2020
KonIQ-10k: An ecologically valid database for deep learning of blind
  image quality assessment
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment
Vlad Hosu
Hanhe Lin
T. Szirányi
Dietmar Saupe
105
567
0
14 Oct 2019
Blind Image Quality Assessment Using A Deep Bilinear Convolutional
  Neural Network
Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
Weixia Zhang
Kede Ma
Jia Yan
Dexiang Deng
Zhou Wang
86
666
0
05 Jul 2019
Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial
  Learning
Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning
Kwan-Yee Lin
Guanxiang Wang
OOD
49
226
0
05 Apr 2018
Feature Pyramid Networks for Object Detection
Feature Pyramid Networks for Object Detection
Nayeon Lee
Piotr Dollár
Ross B. Girshick
Kaiming He
Bharath Hariharan
Serge J. Belongie
ObjD
468
22,108
0
09 Dec 2016
Deep Neural Networks for No-Reference and Full-Reference Image Quality
  Assessment
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
S. Bosse
Dominique Maniry
K. Müller
Thomas Wiegand
Wojciech Samek
77
995
0
06 Dec 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Massive Online Crowdsourced Study of Subjective and Objective Picture
  Quality
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
Deepti Ghadiyaram
A. Bovik
57
660
0
09 Nov 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,386
0
04 Sep 2014
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