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No-Reference Image Quality Assessment (NR-IQA) focuses on designing methods to measure image quality in alignment with human perception when a high-quality reference image is unavailable.
Final Report from the Video Quality Experts Group on the Validation of Objective Models of Video Quality Assessment
Video Quality Experts Group · 2000
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A Fast Algorithm for Multilevel Thresholding
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A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
Hamid R Sheikh, Muhammad F Sabir, and Alan C Bovik · 2006
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Visualizing Data Using t-SNE
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Most Apparent Distortion: Full-Reference Image Quality Assessment and the Role of Strategy
Eric C Larson and Damon M Chandler · 2010
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Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
Deepti Ghadiyaram and Alan C Bovik · 2015
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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, et al · 2015
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A Feature-Enriched Completely Blind Image Quality Evaluator
Lin Zhang, Lei Zhang, and Alan C Bovik · 2015
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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YFCC100M: The New Data in Multimedia Research
Bart Thomee, David A Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li · 2016
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RankIQA: Learning from Rankings for No-Reference Image Quality Assessment
Xialei Liu, Joost Van De Weijer, and Andrew D Bagdanov · 2017
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Decoupled Weight Decay Regularization
Ilya Loshchilov and Frank Hutter · 2017
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Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Blind Image Quality Assessment using a Deep Bilinear Convolutional Neural Network
Weixia Zhang, Kede Ma, Jia Yan, Dexiang Deng, and Zhou Wang · 2018
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No-Reference Image Quality Assessment with Reinforcement Recursive List-Wise Ranking
Jie Gu, Gaofeng Meng, Cheng Da, Shiming Xiang, and Chunhong Pan · 2019
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KADID-10k: A Large-scale Artificially Distorted IQA Database
Hanhe Lin, Vlad Hosu, and Dietmar Saupe · 2019
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Assessing Image Quality Issues for Real-World Problems
Tai-Yin Chiu, Yinan Zhao, and Danna Gurari · 2020
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Perceptual Quality Assessment of Smartphone Photography
Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, and Zhou Wang · 2020
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KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment
V. Hosu, H. Lin, T. Sziranyi, and D. Saupe · 2020
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PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration
Gu Jinjin, Cai Haoming, Chen Haoyu, Ye Xiaoxing, Jimmy S Ren, and Dong Chao · 2020
Cited alongside, same era.
Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network
Iterative Prompt Learning for Unsupervised Backlit Image Enhancement
Zhexin Liang, Chongyi Li, Shangchen Zhou, Ruicheng Feng, and Chen Change Loy · 2023
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Controlling Vision-Language Models for Universal Image Restoration
Ziwei Luo, Fredrik K Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B Schön · 2023
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Test Time Adaptation for Blind Image Quality Assessment
Subhadeep Roy, Shankhanil Mitra, Soma Biswas, and Rajiv Soundararajan · 2023
Later among the works it cites.
Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
Avinab Saha, Sandeep Mishra, and Alan C Bovik · 2023
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SuS-X: Training-Free Name-Only Transfer of Vision-Language Models
Vishaal Udandarao, Ankush Gupta, and Samuel Albanie · 2023
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Shaolin Su, Qingsen Yan, Yu Zhu, Cheng Zhang, Xin Ge, Jinqiu Sun, and Yanning Zhang · 2020
Cited alongside, same era.
From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
Zhenqiang Ying, Haoran Niu, Praful Gupta, Dhruv Mahajan, Deepti Ghadiyaram, and Alan Bovik · 2020
Cited alongside, same era.
Learning Transferable Visual Models from Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
S Alireza Golestaneh, Saba Dadsetan, and Kris M Kitani · 2022
Cited alongside, same era.
Image Quality Assessment Using Contrastive Learning
Pavan C Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, and Alan C Bovik · 2022
Cited alongside, same era.
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Content-Diverse Comparisons Improve IQA
William Thong, Jose Costa Pereira, Sarah Parisot, Ales Leonardis, and Steven McDonagh · 2022
Cited alongside, same era.
Jianyi Wang, Kelvin CK Chan, and Chen Change Loy · 2023
Later among the works it cites.
Depicting Beyond Scores: Advancing Image Quality Assessment Through Multi-Modal Language Models
Zhiyuan You, Zheyuan Li, Jinjin Gu, Zhenfei Yin, Tianfan Xue, and Chao Dong · 2023
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Quality-Aware Pre-Trained Models for Blind Image Quality Assessment
Kai Zhao, Kun Yuan, Ming Sun, Mading Li, and Xing Wen · 2023
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Opinion-Unaware Blind Image Quality Assessment using Multi-Scale Deep Feature Statistics
Zhangkai Ni, Yue Liu, Keyan Ding, Wenhan Yang, Hanli Wang, and Shiqi Wang · 2024
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Transformer-based No-Reference Image Quality Assessment via Supervised Contrastive Learning
Jinsong Shi, Pan Gao, and Jie Qin · 2024
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Blind Image Quality Assessment Based on Geometric Order Learning
Nyeong-Ho Shin, Seon-Ho Lee, and Chang-Su Kim · 2024
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Opinion Unaware Image Quality Assessment via Adversarial Convolutional Variational Autoencoder
Ankit Shukla, Avinash Upadhyay, Swati Bhugra, and Manoj Sharma · 2024
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Learning Generalizable Perceptual Representations for Data-Efficient No-Reference Image Quality Assessment
Suhas Srinath, Shankhanil Mitra, Shika Rao, and Rajiv Soundararajan · 2024
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Boosting Image Quality Assessment through Efficient Transformer Adaptation with Local Feature Enhancement
Kangmin Xu, Liang Liao, Jing Xiao, Chaofeng Chen, Haoning Wu, Qiong Yan, and Weisi Lin · 2024
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Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini, and Andrew D. Bagdanov · 2025
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