mlsanityData to 7 Oct 2026

Q-Refine: A Perceptual Quality Refiner for AI-Generated Image

arXiv 2401.01117 ↗First posted 2 Jan 2024cs.CV eess.IVcited by 21

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Abstract (arXiv)

With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge. However, uniformly refining AI-Generated Images (AIGIs) of different qualities not only limited optimization capabilities for low-quality AIGIs but also brought negative optimization to high-quality AIGIs. To address this issue, a quality-award refiner named Q-Refine is proposed. Based on the preference of the Human Visual System (HVS), Q-Refine uses the Image Quality Assessment (IQA) metric to guide the refining process for the first time, and modify images of different qualities through three adaptive pipelines. Experimental shows that for mainstream T2I models, Q-Refine can perform effective optimization to AIGIs of different qualities. It can be a general refiner to optimize AIGIs from both fidelity and aesthetic quality levels, thus expanding the application of the T2I generation models.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 27 of its 43 references that are in the map. First posted on arXiv 2 Jan 2024.

Builds on

27 of 43 references.

References · 27

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  4. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  5. 2022Exploring CLIP for Assessing the Look and Feel of Imagescited by 974
  6. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 854
  7. 2023Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levelscited by 489
  8. 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
  9. 2023DiffBIR: Towards Blind Image Restoration with Generative Diffusion Priorcited by 255
  10. 2023Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Visioncited by 247
  11. 2019From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Qualitycited by 221
  12. 2023Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Modelscited by 152
15 more
  1. 2023AGIQA-3K: An Open Database for AI-Generated Image Quality Assessmentcited by 142
  2. 2020Residual Feature Distillation Network for Lightweight Image Super-Resolutioncited by 122
  3. 2020Unsupervised Real-world Image Super Resolution via Domain-distance Aware Trainingcited by 83
  4. 2022Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Modelscited by 63
  5. 2023AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and Correspondencecited by 61
  6. 2023A Perceptual Quality Assessment Exploration for AIGC Imagescited by 54
  7. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  8. 2022Best Prompts for Text-to-Image Models and How to Find Themcited by 35
  9. 2023Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluationcited by 27
  10. 2023VDPVE: VQA Dataset for Perceptual Video Enhancementcited by 22
  11. 2023Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Modelscited by 22
  12. 2023GMS-3DQA: Projection-based Grid Mini-patch Sampling for 3D Model Quality Assessmentcited by 20
  13. 2023StableVQA: A Deep No-Reference Quality Assessment Model for Video Stabilitycited by 15
  14. 2023A real-time blind quality-of-experience assessment metric for HTTP adaptive streamingcited by 5
  15. 2023XGC-VQA: A unified video quality assessment model for User, Professionally, and Occupationally-Generated Contentcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 14; 2025: 5; 2026: 2.

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  1. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  2. 2024Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessmentcited by 39
  3. 2024AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessmentcited by 33
  4. 2024MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Modelcited by 29
  5. 2024R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?cited by 29
  6. 2024Quality Assessment in the Era of Large Models: A Surveycited by 26
  7. 2024Large Multi-modality Model Assisted AI-Generated Image Quality Assessmentcited by 24
  8. 2024NTIRE 2024 Quality Assessment of AI-Generated Content Challengecited by 20
  9. 2025Image Quality Assessment: From Human to Machine Preferencecited by 12
  10. 2024G-Refine: A General Quality Refiner for Text-to-Image Generationcited by 8
  11. 2025MoEdit: On Learning Quantity Perception for Multi-object Image Editingcited by 7
  12. 2024Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidancecited by 6
9 more
  1. 2024CMC-Bench: Towards a New Paradigm of Visual Signal Compressioncited by 6
  2. 2025Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Schedulingcited by 3
  3. 2025Q-Save: Towards Scoring and Attribution for Generated Video Evaluationcited by 3
  4. 2024LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agentscited by 2
  5. 2024D-Judge: How Far Are We? Assessing the Discrepancies Between AI-synthesized and Natural Images through Multimodal Guidancecited by 1
  6. 2025RePack then Refine: Efficient Diffusion Transformer with Vision Foundation Modelcited by 1
  7. 2026rPPG-VQA: A Video Quality Assessment Framework for Unsupervised rPPG Trainingcited by 1
  8. 2024IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Modelscited by 0
  9. 2026SynerDiff: Synergetic Continuous Batching for Fast and Parallel Diffusion Model Inferencecited by 0