mlsanityData to 7 Oct 2026

RankIQA: Learning from Rankings for No-reference Image Quality Assessment

arXiv 1707.08347 ↗First posted 26 Jul 2017cs.CVcited by 150

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Abstract (arXiv)

We propose a no-reference image quality assessment (NR-IQA) approach that learns from rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese Network to rank images in terms of image quality by using synthetically generated distortions for which relative image quality is known. These ranked image sets can be automatically generated without laborious human labeling. We then use fine-tuning to transfer the knowledge represented in the trained Siamese Network to a traditional CNN that estimates absolute image quality from single images. We demonstrate how our approach can be made significantly more efficient than traditional Siamese Networks by forward propagating a batch of images through a single network and backpropagating gradients derived from all pairs of images in the batch. Experiments on the TID2013 benchmark show that we improve the state-of-the-art by over 5%. Furthermore, on the LIVE benchmark we show that our approach is superior to existing NR-IQA techniques and that we even outperform the state-of-the-art in full-reference IQA (FR-IQA) methods without having to resort to high-quality reference images to infer IQA.

Key facts. Cited by 150 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jul 2017.

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Citing papers per year: 2021: 19; 2022: 28; 2023: 19; 2024: 35; 2025: 29; 2026: 20.

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  1. 2023Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspectivecited by 276
  2. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
  3. 2021No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistencycited by 165
  4. 2025Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distributioncited by 139
  5. 2023Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Modelscited by 104
  6. 2025Q-Insight: Understanding Image Quality via Visual Reinforcement Learningcited by 93
  7. 2024Towards Open-ended Visual Quality Comparisoncited by 85
  8. 2025VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rankcited by 77
  9. 2021CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiabilitycited by 68
  10. 2024Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Comparecited by 66
  11. 2022Underwater Ranker: Learn Which Is Better and How to Be Bettercited by 65
  12. 2024Diffusion Models, Image Super-Resolution And Everything: A Surveycited by 63
38 more
  1. 2024EvaGaussians: Event Stream Assisted Gaussian Splatting from Blurry Imagescited by 56
  2. 2024Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Datasetcited by 38
  3. 2021Continual Learning for Blind Image Quality Assessmentcited by 36
  4. 2024Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessmentcited by 31
  5. 2021A Comprehensive Review of Deep Learning-based Single Image Super-resolutioncited by 23
  6. 2022Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Modelcited by 22
  7. 2022Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advancescited by 21
  8. 2021Task-Specific Normalization for Continual Learning of Blind Image Quality Modelscited by 18
  9. 2023Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attackscited by 18
  10. 2024PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wildcited by 17
  11. 2021No-Reference Image Quality Assessment by Hallucinating Pristine Featurescited by 16
  12. 2024MotionStone: Decoupled Motion Intensity Modulation with Diffusion Transformer for Image-to-Video Generationcited by 16
  13. 2021A strong baseline for image and video quality assessmentcited by 15
  14. 2023Quality-aware Pre-trained Models for Blind Image Quality Assessmentcited by 15
  15. 2021Region-Adaptive Deformable Network for Image Quality Assessmentcited by 14
  16. 2023Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial Attackscited by 14
  17. 2023PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated Imagescited by 14
  18. 2024PromptIQA: Boosting the Performance and Generalization for No-Reference Image Quality Assessment via Promptscited by 14
  19. 2024CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIPcited by 14
  20. 2021RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rankcited by 13
  21. 2021Assessing a Single Image in Reference-Guided Image Synthesiscited by 13
  22. 2024VisualCritic: Making LMMs Perceive Visual Quality Like Humanscited by 13
  23. 2024SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuningcited by 13
  24. 2021A Deep Insight into Measuring Face Image Utility with General and Face-specific Image Quality Metricscited by 12
  25. 2024GraFIQs: Face Image Quality Assessment Using Gradient Magnitudescited by 12
  26. 2024Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessmentcited by 12
  27. 2023Test Time Adaptation for Blind Image Quality Assessmentcited by 11
  28. 2023Always Clear Days: Degradation Type and Severity Aware All-In-One Adverse Weather Removalcited by 11
  29. 2023Learning Generalizable Perceptual Representations for Data-Efficient No-Reference Image Quality Assessmentcited by 11
  30. 2021Continual learning in cross-modal retrievalcited by 10
  31. 2022MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusioncited by 10
  32. 2022Source-free Unsupervised Domain Adaptation for Blind Image Quality Assessmentcited by 9
  33. 2022StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessmentcited by 9
  34. 2024Bridging the Synthetic-to-Authentic Gap: Distortion-Guided Unsupervised Domain Adaptation for Blind Image Quality Assessmentcited by 9
  35. 2021Subjective and Objective Quality Assessment of Mobile Gaming Videocited by 8
  36. 2022Deep Rotation Correction without Angle Priorcited by 8
  37. 2022Face Morphing Attacks and Face Image Quality: The Effect of Morphing and the Unsupervised Attack Detection by Qualitycited by 8
  38. 2023On the Effectiveness of Spectral Discriminators for Perceptual Quality Improvementcited by 8

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