mlsanityData to 7 Oct 2026

A Perceptual Quality Assessment Exploration for AIGC Images

arXiv 2303.12618 ↗First posted 22 Mar 2023cs.CV eess.IVcited by 54

Not on the map. Why?

Abstract (arXiv)

underlineAI underlineGenerated underlineContent (AIGC) has gained widespread attention with the increasing efficiency of deep learning in content creation. AIGC, created with the assistance of artificial intelligence technology, includes various forms of content, among which the AI-generated images (AGIs) have brought significant impact to society and have been applied to various fields such as entertainment, education, social media, etc. However, due to hardware limitations and technical proficiency, the quality of AIGC images (AGIs) varies, necessitating refinement and filtering before practical use. Consequently, there is an urgent need for developing objective models to assess the quality of AGIs. Unfortunately, no research has been carried out to investigate the perceptual quality assessment for AGIs specifically. Therefore, in this paper, we first discuss the major evaluation aspects such as technical issues, AI artifacts, unnaturalness, discrepancy, and aesthetics for AGI quality assessment. Then we present the first perceptual AGI quality assessment database, AGIQA-1K, which consists of 1,080 AGIs generated from diffusion models. A well-organized subjective experiment is followed to collect the quality labels of the AGIs. Finally, we conduct a benchmark experiment to evaluate the performance of current image quality assessment (IQA) models.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). Builds on 9 of its 33 references that are in the map. First posted on arXiv 22 Mar 2023.

Builds on

9 of 33 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2022Generative Adversarial Networkscited by 5,603
  5. 2017NIMA: Neural Image Assessmentcited by 387
  6. 2019KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentcited by 351
  7. 2019From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Qualitycited by 221
  8. 2016Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approachcited by 71
  9. 2019No-Reference Quality Assessment of Contrast-Distorted Images using Contrast Enhancementcited by 14

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 24; 2025: 14; 2026: 5.

54 papers.

Sort:

By area:

  1. 2023Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesiscited by 847
  2. 2023AGIQA-3K: An Open Database for AI-Generated Image Quality Assessmentcited by 142
  3. 2025Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distributioncited by 139
  4. 2024Learning Multi-dimensional Human Preference for Text-to-Image Generationcited by 102
  5. 2024AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perceptioncited by 63
  6. 2024Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessmentcited by 39
  7. 2024AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessmentcited by 33
  8. 2024Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessmentcited by 31
  9. 2023Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluationcited by 27
  10. 2024Quality Assessment in the Era of Large Models: A Surveycited by 26
  11. 2023Exploring the Naturalness of AI-Generated Imagescited by 22
  12. 2024Q-Refine: A Perceptual Quality Refiner for AI-Generated Imagecited by 21
38 more
  1. 2024NTIRE 2024 Quality Assessment of AI-Generated Content Challengecited by 20
  2. 2023StableVQA: A Deep No-Reference Quality Assessment Model for Video Stabilitycited by 15
  3. 2024SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Modelcited by 15
  4. 2024Video Quality Assessment: A Comprehensive Surveycited by 15
  5. 2023PKU-I2IQA: An Image-to-Image Quality Assessment Database for AI Generated Imagescited by 14
  6. 2023Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancementcited by 12
  7. 2024Bringing Textual Prompt to AI-Generated Image Quality Assessmentcited by 12
  8. 2025Image Quality Assessment: From Human to Machine Preferencecited by 12
  9. 2023PSCR: Patches Sampling-based Contrastive Regression for AIGC Image Quality Assessmentcited by 10
  10. 2024Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessmentcited by 10
  11. 2023An Overview on Generative AI at Scale with Edge-Cloud Computingcited by 9
  12. 2024Vision-Language Consistency Guided Multi-modal Prompt Learning for Blind AI Generated Image Quality Assessmentcited by 9
  13. 2025NTIRE 2025 challenge on Text to Image Generation Model Quality Assessmentcited by 8
  14. 2024TIER: Text-Image Encoder-based Regression for AIGC Image Quality Assessmentcited by 7
  15. 2025MoEdit: On Learning Quantity Perception for Multi-object Image Editingcited by 7
  16. 2024Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidancecited by 6
  17. 2024CMC-Bench: Towards a New Paradigm of Visual Signal Compressioncited by 6
  18. 2025Text-Visual Semantic Constrained AI-Generated Image Quality Assessmentcited by 6
  19. 2024AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similaritycited by 5
  20. 2024Few-Shot Image Quality Assessment via Adaptation of Vision-Language Modelscited by 4
  21. 2026Decoupling Semantics from Distortions: Multi-Scale Two-Stream Vision-Language Alignment for AI-Generated Image Quality Assessmentcited by 4
  22. 2024Image and Video Quality Assessment using Prompt-Guided Latent Diffusion Models for Cross-Dataset Generalizationcited by 3
  23. 2024Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunitiescited by 3
  24. 2025M3-AGIQA: Multimodal, Multi-Round, Multi-Aspect AI-Generated Image Quality Assessmentcited by 2
  25. 2025Multi-Dimensional Quality Assessment for Text-to-3D Assets: Dataset and Modelcited by 2
  26. 2025Plug In, Grade Right: Psychology-Inspired AGIQAcited by 2
  27. 2023Offloading and Quality Control for AI Generated Content Services in 6G Mobile Edge Computing Networkscited by 1
  28. 2024Advancing Video Quality Assessment for AIGCcited by 1
  29. 2024D-Judge: How Far Are We? Assessing the Discrepancies Between AI-synthesized and Natural Images through Multimodal Guidancecited by 1
  30. 2025InstructEngine: Instruction-driven Text-to-Image Alignmentcited by 1
  31. 2025RAISE: Realness Assessment for Image Synthesis and Evaluationcited by 1
  32. 2023FERGI: Automatic Scoring of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reactioncited by 0
  33. 2024PKU-AIGIQA-4K: A Perceptual Quality Assessment Database for Both Text-to-Image and Image-to-Image AI-Generated Imagescited by 0
  34. 2024ReFeR: Improving Evaluation and Reasoning through Hierarchy of Modelscited by 0
  35. 2025Hierarchical Fusion and Joint Aggregation: A Multi-Level Feature Representation Method for AIGC Image Quality Assessmentcited by 0
  36. 2025AU-IQA: A Benchmark Dataset for Perceptual Quality Assessment of AI-Enhanced User-Generated Contentcited by 0
  37. 2025Image Realness Assessment and Localization with Multimodal Featurescited by 0
  38. 2025Beyond Pixels: Benchmarking and Reward-Based Assessing Framework for Visual Spatial Aestheticscited by 0

50 most cited of 54 All 54 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2025Towards Explainable Partial-AIGC Image Quality Assessment
  2. 2024PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition
  3. 2025AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images
  4. 2024AI-generated Image Quality Assessment in Visual Communication
  5. 2024CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIP
  6. 2025ViDA-UGC: Detailed Image Quality Analysis via Visual Distortion Assessment for UGC Images
  7. 2024Large Multi-modality Model Assisted AI-Generated Image Quality Assessment
  8. 2024Visual Verity in AI-Generated Imagery: Computational Metrics and Human-Centric Analysis