mlsanityData to 7 Oct 2026

NIMA: Neural Image Assessment

arXiv 1709.05424 ↗First posted 15 Sep 2017cs.CVcited by 387

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Cited by 35 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Automatically learned quality assessment for images has recently become a hot topic due to its usefulness in a wide variety of applications such as evaluating image capture pipelines, storage techniques and sharing media. Despite the subjective nature of this problem, most existing methods only predict the mean opinion score provided by datasets such as AVA [1] and TID2013 [2]. Our approach differs from others in that we predict the distribution of human opinion scores using a convolutional neural network. Our architecture also has the advantage of being significantly simpler than other methods with comparable performance. Our proposed approach relies on the success (and retraining) of proven, state-of-the-art deep object recognition networks. Our resulting network can be used to not only score images reliably and with high correlation to human perception, but also to assist with adaptation and optimization of photo editing/enhancement algorithms in a photographic pipeline. All this is done without need for a "golden" reference image, consequently allowing for single-image, semantic- and perceptually-aware, no-reference quality assessment.

Key facts. Cited by 387 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Sep 2017.

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Citing papers per year: 2020: 1; 2021: 48; 2022: 47; 2023: 57; 2024: 69; 2025: 84; 2026: 81.

387 papers.

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  1. 2021MUSIQ: Multi-scale Image Quality Transformercited by 1,058
  2. 2022MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessmentcited by 514
  3. 2023Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levelscited by 489
  4. 2022MaxViT: Multi-Axis Vision Transformercited by 476
  5. 2022Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectivescited by 314
  6. 2023Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Visioncited by 247
  7. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
  8. 2021A Survey of Human-in-the-loop for Machine Learningcited by 214
  9. 2021No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistencycited by 165
  10. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  11. 2023AGIQA-3K: An Open Database for AI-Generated Image Quality Assessmentcited by 142
  12. 2025Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distributioncited by 139
38 more
  1. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  2. 2025Q-Insight: Understanding Image Quality via Visual Reinforcement Learningcited by 93
  3. 2025VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rankcited by 77
  4. 2023RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priorscited by 73
  5. 2023Content-based Unrestricted Adversarial Attackcited by 73
  6. 2023Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bankcited by 68
  7. 2022Underwater Ranker: Learn Which Is Better and How to Be Bettercited by 65
  8. 2024Instruct-Imagen: Image Generation with Multi-modal Instructioncited by 65
  9. 2021Making Images Real Again: A Comprehensive Survey on Deep Image Compositioncited by 63
  10. 2023VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretrainingcited by 63
  11. 2024Diffusion Models, Image Super-Resolution And Everything: A Surveycited by 63
  12. 2021Mobile Computational Photography: A Tourcited by 62
  13. 2022SinDDM: A Single Image Denoising Diffusion Modelcited by 60
  14. 2023Uni-paint: A Unified Framework for Multimodal Image Inpainting with Pretrained Diffusion Modelcited by 60
  15. 2024Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restorationcited by 60
  16. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  17. 2023A Perceptual Quality Assessment Exploration for AIGC Imagescited by 54
  18. 2022DeepPrivacy2: Towards Realistic Full-Body Anonymizationcited by 51
  19. 2023Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Methodcited by 48
  20. 2024MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Spacecited by 48
  21. 2025CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Modelscited by 47
  22. 2021Learning to Resize Images for Computer Vision Taskscited by 45
  23. 2021Early Stopping for Deep Image Priorcited by 44
  24. 2021Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessmentcited by 41
  25. 2022NTIRE 2022 Challenge on Perceptual Image Quality Assessmentcited by 41
  26. 2024UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmarkcited by 39
  27. 2022Natural Color Fool: Towards Boosting Black-box Unrestricted Attackscited by 38
  28. 2024Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Drivingcited by 35
  29. 2022Few-shot Image Generation via Adaptation-Aware Kernel Modulationcited by 33
  30. 2023A Large-Scale Outdoor Multi-modal Dataset and Benchmark for Novel View Synthesis and Implicit Scene Reconstructioncited by 32
  31. 2024Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restorationcited by 32
  32. 2021PhotoWCT2: Compact Autoencoder for Photorealistic Style Transfer Resulting from Blockwise Training and Skip Connections of High-Frequency Residualscited by 30
  33. 2022Video compression dataset and benchmark of learning-based video-quality metricscited by 27
  34. 2024Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Networkcited by 26
  35. 2024Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolutioncited by 25
  36. 2021A Comprehensive Review of Deep Learning-based Single Image Super-resolutioncited by 23
  37. 2023Image Super-Resolution with Text Prompt Diffusioncited by 22
  38. 2024OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones?cited by 22

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