Image Quality Assessment

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Image Quality Assessment asks how good, degraded, or useful an image appears, often when no pristine reference is available, and matters for choosing, improving, or safely using images. Methods range from full-reference metrics such as PSNR and SSIM to no-reference neural predictors, human preference models, and vision-language systems that explain or localize defects. Work increasingly targets specific settings—including generated and restored images, compression, medical scans, and scientific imagery—and uses subjective benchmarks, cross-dataset tests, and downstream task performance. A central tension is that pixel fidelity, human perception, semantic correctness, and task utility can disagree, while models may lose reliability across domains, distortions, or evaluation protocols.

Latest papers

168 papers17 papers in the last four weeks, up 13% on the four weeks before. 0.1% of all new papers.

Subspace-Guided Semantic and Topological Invariant Registration for Annotation-Free Ultrasound Plane Quality Control
May 25, 2026Chunzheng Zhu, Jianxin Lin, Feng Wang +5Ultrasound Imaging Image Quality Assessment
Hunan University, Changsha, China · Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
IQA-Spider: Unifying Multi-Granularity Image Quality Assessment with Reasoning, Grounding and Referring
May 23, 2026Xinge Peng, Yiting Lu, Xin Li +1VLM Reasoning Image Quality Assessment
University of Science and Technology of China, Hefei, China.
Ultra-High-Definition Image Quality Assessment via Graph Representation Learning
May 21, 2026Shaode Yu, Enqi Chen, Ming Huang +4Image Quality Assessment
School of Information and Communication Engineering, Communication University of China, Beijing 100024, China · College of Engineering, Northeastern University, Silicon Valley, San Jose, CA 95113, USA · JancsiLab, JancsiTech, Hongkong 999077, China +1
SR-Ground: Image Quality Grounding for Super-Resolved Content
May 20, 2026Artem Borisov, Evgeney Bogatyrev, Khaled Abud +1Image Quality Assessment Image Super-Resolution
Lomonosov Moscow State University Moscow, Russia · MSU AI Center, Lomonosov Moscow State University Moscow, Russia
HAPS: Rethinking Image Similarity for Virtual Staining
May 19, 2026Fedor Gubanov, Svetlana Illarionova, Vlad Kozlovskiy +6Computational Pathology Medical Image Analysis
1*Skolkovo Institute of Science and Technology, Moscow, 121205, Russia. · 2BIMAI-Lab, Biomedically Informed Artificial Intelligence Laboratory,2026 University of Sharjah, Sharjah, United Arab Emirates. · 3National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Moscow, Russia.
Preferences Order, Ratings Anchor: From Fused Expert Aesthetic Ground Truth to Self-Distillation
May 19, 2026Yuanpei Zhao, Jie Lin, Chao Zhang +5Pairwise Preference Learning Personalized Image Aesthetics Assessment
1Sichuan University · 2NetEase Fuxi AI Lab · †Work done during an internship at NetEase Fuxi AI Lab. +1
iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment
May 19, 2026Xinli Yue, JianHui Sun, Tao Shao +3Pairwise Comparison Image Quality Assessment
WeChat, Tencent
Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction
May 18, 2026Yu Li, Puchao Zhou, Yachun Mi +3Vision Transformer Vision Foundation Model Adaptation
Harbin Institute of Technology · Meituan
MSIQ: Moment-based Scale-Invariant Quality Measure for Single Image Super-Resolution
May 17, 2026Leonid BedratyukImage Quality Assessment Image Super-Resolution
Employing Vision-Language Models for Face Image Quality Assessment
May 17, 2026Erdi Sarıtaş, Eren Onaran, Vitomir Štruc +1VLM Evaluation VLM Robustness
Department of Computer Engineering, Istanbul Technical University, Istanbul, Türkiye · Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia · Division of Engineering, NYU Abu Dhabi, Abu Dhabi, UAE
CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
May 14, 2026Yousra Nabila Taifour, Marouane Tliba, Zuheng Ming +9Image Quality Assessment Computed Tomography
1Université Sorbonne Paris Nord · University of Dubai · 3Northwestern University +3
SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation
May 14, 2026Ivan Molodetskikh, Kirill Malyshev, Mark Mirgaleev +3Image Quality Assessment Image Super-Resolution
AI Center, Lomonosov Moscow State University, GSP-1, Leninskie Gory, Moscow, 119991, Russia · Lomonosov Moscow State University
AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction
May 14, 2026Yoshia Abe, Tatsuya Daikoku, Yasuo KuniyoshiPersonalized Image Aesthetics Assessment Image Quality Assessment
Graduate School of Information Science and Technology The University of Tokyo Bunkyo-ku, Tokyo 113-8654, Japan
PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media
May 14, 2026Fuhao Li, Shaofeng You, Jiagao Hu +6Image Editing Evaluation Video Editing
MiLM Plus, Xiaomi Inc.
PreFIQs: Face Image Quality Is What Survives Pruning
May 13, 2026Jan Niklas Kolf, Guray Ozgur, Andrea Atzori +4Image Quality Assessment
FRAUNHOFER INSTITUTE FOR COMPUTER GRAPHICS RESEARCH IGD, GERMANY · TECHNICAL UNIVERSITY OF DARMSTADT, GERMANY · UNIVERSITY OF LJUBLJANA, SLOVENIA
Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?
May 12, 2026Yichen Feng, Yuetai Li, Chunjiang Liu +14Multimodal Large Language Models Image Quality Assessment
SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models
May 11, 2026Chen Zhong, Xiao An, Jiaxing Sun +3VLM Evaluation Remote Sensing
Wuhan University · Shanghai Artificial Intelligent Laboratory
ML-CLIPSim: Multi-Layer CLIP Similarity for Machine-Oriented Image Quality
May 10, 2026Feng Ding, Haisheng Fu, Jie Liang +3Image Quality Assessment
Simon Fraser University · University of British Columbia · Eastern Institute of Technology +2
APEX: Assumption-free Projection-based Embedding eXamination Metric for Generative Distribution Evaluation
May 8, 2026Caterina Gallegati, Monica Bianchini, Franco Scarselli +2Image Quality Assessment Image Generation Evaluation
University of Siena, Italy · AI for Good (AIGO), Istituto Italiano di Tecnologia, Italy · University of Verona, Italy
Bringing Multimodal Large Language Models to Infrared-Visible Image Fusion Quality Assessment
May 7, 2026Yuchen Guo, Junli Gong, Yao Lu +3Infrared-Visible Image Fusion Learning to Rank
Northwestern University · Northeastern University · University of Washington +2
Pixel Perfect: Relational Image Quality Assessment with Spatially-Aware Distortions
May 4, 2026Fadeel Sher Khan, Long N. Le, Abhinau K. Venkataramanan +2Image Quality Assessment
The University of Texas at Austin Austin, TX, USA · Samsung Research America Plano, TX, USA
Beyond Fidelity: Semantic Similarity Assessment in Low-Level Image Processing
Apr 28, 2026Runjie Wang, Weiling Chen, Tiesong Zhao +1Image Quality Assessment
Fuzhou University Fuzhou, Fujian, China · The Hong Kong Polytechnic University Hong Kong, China
Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Unified and Generalized Approach
Apr 27, 2026Jiebin Yan, Kangcheng Wu, Jingwen Hou +3Image Quality Assessment
School of Computing and Artificial Intelligence, Jiangxi University of Finance and Economics, Nanchang 330032, Jiangxi, China, and also with the Jiangxi AI Quality Testing and Inspection Center, Nanchang 330029, Jiangxi, China · School of Artificial Intelligence, Xidian University, Xi’an, China
Causal Disentanglement-Inspired Degradation Representation Learning for Full-Reference Image Quality Assessment
Apr 23, 2026Zhen Zhang, Jielei Chu, Tian Zhang +5Disentangled Representation Learning Image Quality Assessment
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China · School of Physics, Northeast Normal University, Changchun 130024, China · School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China +2
DistortBench: Benchmarking Vision Language Models on Image Distortion Identification
Apr 21, 2026Divyanshu Goyal, Akhil Eppa, Vanya Bannihatti KumarVLM Evaluation Benchmark Construction
Adobe Inc.
EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment
Apr 21, 2026Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +4Efficient Transformer Inference Efficient Inference
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany · Department of Computer Science, TU Darmstadt, Germany
ATTN-FIQA: Interpretable Attention-based Face Image Quality Assessment with Vision Transformers
Apr 21, 2026Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +5Image Quality Assessment
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany · Department of Computer Science, TU Darmstadt, Germany
MSDS: Deep Structural Similarity with Multiscale Representation
Apr 21, 2026Danling Kang, Xue-Hua Chen, Bin Liu +3Multi-Scale Feature Fusion Image Quality Assessment
Fujian Key Lab for Intelligent Processing and Wireless Communication of Media Information, College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China · School of Computing and Information Science, Fuzhou Institute of Technology, Fuzhou 350506, China · School of Electronic Engineering, Fuzhou Inistitute of Technology, Fuzhou 350506, China +1
Enhancing Zero-shot Personalized Image Aesthetics Assessment with Profile-aware Multimodal LLM
Apr 19, 2026Chun Wang, Chenfeng Wei, Chenyang Liu +1Zero-Shot Learning Personalized Image Aesthetics Assessment
Mashang Consumer Finance Co., Ltd., Chongqing, China · Xi’an Jiaotong-Liverpool University, Suzhou, China · Beijing University of Posts and Telecommunications, Beijing, China
Q-DeepSight: Incentivizing Thinking with Images for Image Quality Assessment and Refinement
Apr 18, 2026Xudong Li, Jiaxi Tan, Ziyin Zhou +6Tool Use in VLMs Multimodal CoT Reasoning
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, 361005, P.R. China · Beijing Institute of Technology

May 25, 2026J/K move · Enter open · S save

Subspace-Guided Semantic and Topological Invariant Registration for Annotation-Free Ultrasound Plane Quality Control

Chunzheng Zhu, Jianxin Lin, Feng Wang, Cheng Jiang+4

Hunan University, Changsha, China · Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China

Ultrasound Imaging Image Quality Assessment

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Reliable quality control (QC) of ultrasound images is essential for both real-time acquisition guidance and retrospective clinical audit, yet existing approaches rely heavily on per-plane annotations, or employ pseudo-labeling prone to systematic bias under spatial deformations inherent in clinical acquisition. We present STRIQ, a registration-driven framework that recasts annotation-free US plane quality control as a subspace-guided consistency measurement problem. Specifically, STRIQ introduces a Latent Registration Aligner (LRA) to establish hierarchical feature space correspondences between query images and variance-driven anchors, which are autonomously distilled from unlabeled data via a variance spectrum criterion to serve as structurally stable prototypes. To further disambiguate anatomical planes and mitigate negative knowledge transfer, we propose an Orthogonal Knowledge Subspace (OKS) module. The OKS decomposes plane-specific representations into mutually orthogonal subspaces, enabling fine-grained expert collaboration while preventing inter-plane interference, ensuring that the quality metric is grounded in principled subspace proximity. Extensive experiments on the in-house US4QA and public CAMUS datasets demonstrate that STRIQ achieves state-of-the-art correlation with clinical quality scores, establishing a new paradigm for annotation-free, real-time reliable ultrasound quality control. Our code is available at https://github.com/zhcz328/STRIQ.