mlsanityData to 14 Oct 2026

Learning a No-Reference Quality Metric for Single-Image Super-Resolution

arXiv 1612.05890 ↗First posted 18 Dec 2016cs.CVcited by 144

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Abstract (arXiv)

Numerous single-image super-resolution algorithms have been proposed in the literature, but few studies address the problem of performance evaluation based on visual perception. While most super-resolution images are evaluated by fullreference metrics, the effectiveness is not clear and the required ground-truth images are not always available in practice. To address these problems, we conduct human subject studies using a large set of super-resolution images and propose a no-reference metric learned from visual perceptual scores. Specifically, we design three types of low-level statistical features in both spatial and frequency domains to quantify super-resolved artifacts, and learn a two-stage regression model to predict the quality scores of super-resolution images without referring to ground-truth images. Extensive experimental results show that the proposed metric is effective and efficient to assess the quality of super-resolution images based on human perception.

Key facts. Cited by 144 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2016.

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Citing papers per year: 2021: 23; 2022: 33; 2023: 31; 2024: 21; 2025: 24; 2026: 12.

144 papers.

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  1. 2022Exploring CLIP for Assessing the Look and Feel of Imagescited by 991
  2. 2021Designing a Practical Degradation Model for Deep Blind Image Super-Resolutioncited by 529
  3. 2022MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessmentcited by 522
  4. 2021GAN Inversion: A Surveycited by 367
  5. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 226
  6. 2021Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimationcited by 192
  7. 2025Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distributioncited by 141
  8. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 134
  9. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 109
  10. 2023Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Modelscited by 105
  11. 2025Q-Insight: Understanding Image Quality via Visual Reinforcement Learningcited by 98
  12. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 97
38 more
  1. 2022LEDNet: Joint Low-light Enhancement and Deblurring in the Darkcited by 96
  2. 2022Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesiscited by 86
  3. 2021Fourier Space Losses for Efficient Perceptual Image Super-Resolutioncited by 73
  4. 2021Real-World Single Image Super-Resolution: A Brief Reviewcited by 65
  5. 2023PromptMagician: Interactive Prompt Engineering for Text-to-Image Creationcited by 58
  6. 2022Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Networkcited by 57
  7. 2021Perceptual Image Quality Assessment with Transformerscited by 54
  8. 2024DarkIR: Robust Low-Light Image Restorationcited by 48
  9. 2022NTIRE 2022 Challenge on Perceptual Image Quality Assessmentcited by 41
  10. 2024Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Datasetcited by 38
  11. 2024RealViformer: Investigating Attention for Real-World Video Super-Resolutioncited by 33
  12. 2021Locally Adaptive Structure and Texture Similarity for Image Quality Assessmentcited by 32
  13. 2024Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessmentcited by 32
  14. 2024Q-Ground: Image Quality Grounding with Large Multi-modality Modelscited by 30
  15. 2021On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Frameworkcited by 27
  16. 2021Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernelcited by 27
  17. 2022Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical Fidelitycited by 24
  18. 2023SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistencycited by 24
  19. 2021A Comprehensive Review of Deep Learning-based Single Image Super-resolutioncited by 23
  20. 2022Learning to Adapt to Lightcited by 21
  21. 2024WaveFace: Authentic Face Restoration with Efficient Frequency Recoverycited by 20
  22. 2021A Systematic Survey of Deep Learning-based Single-Image Super-Resolutioncited by 19
  23. 2022Perception-Distortion Balanced ADMM Optimization for Single-Image Super-Resolutioncited by 19
  24. 2021NTIRE 2021 Challenge on Perceptual Image Quality Assessmentcited by 18
  25. 2022Self-Supervised Image Restoration with Blurry and Noisy Pairscited by 17
  26. 2023Generating Aligned Pseudo-Supervision from Non-Aligned Data for Image Restoration in Under-Display Cameracited by 16
  27. 2024Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifactscited by 16
  28. 2021Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalnesscited by 15
  29. 2021Region-Adaptive Deformable Network for Image Quality Assessmentcited by 14
  30. 2021ERQA: Edge-Restoration Quality Assessment for Video Super-Resolutioncited by 14
  31. 2021A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolutioncited by 14
  32. 2022Deep Neural Network for Blind Visual Quality Assessment of 4K Contentcited by 14
  33. 2021RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rankcited by 13
  34. 2022Optimally Controllable Perceptual Lossy Compressioncited by 13
  35. 2022MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-Resolutioncited by 13
  36. 2023VQCNIR: Clearer Night Image Restoration with Vector-Quantized Codebookcited by 13
  37. 2022Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessmentcited by 12
  38. 2023Expanding Synthetic Real-World Degradations for Blind Video Super Resolutioncited by 12

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