mlsanityData to 7 Oct 2026

GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

arXiv 2012.00739 ↗First posted 1 Dec 2020cs.CVcited by 158

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Cited by 44 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We show that pre-trained Generative Adversarial Networks (GANs), e.g., StyleGAN, can be used as a latent bank to improve the restoration quality of large-factor image super-resolution (SR). While most existing SR approaches attempt to generate realistic textures through learning with adversarial loss, our method, Generative LatEnt bANk (GLEAN), goes beyond existing practices by directly leveraging rich and diverse priors encapsulated in a pre-trained GAN. But unlike prevalent GAN inversion methods that require expensive image-specific optimization at runtime, our approach only needs a single forward pass to generate the upscaled image. GLEAN can be easily incorporated in a simple encoder-bank-decoder architecture with multi-resolution skip connections. Switching the bank allows the method to deal with images from diverse categories, e.g., cat, building, human face, and car. Images upscaled by GLEAN show clear improvements in terms of fidelity and texture faithfulness in comparison to existing methods.

Key facts. Cited by 158 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Dec 2020.

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Citing papers per year: 2021: 13; 2022: 47; 2023: 38; 2024: 36; 2025: 17; 2026: 7.

158 papers.

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  1. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  2. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 961
  3. 2022Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Modelcited by 574
  4. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolutioncited by 486
  5. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shiftingcited by 360
  6. 2024Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wildcited by 281
  7. 2023DiffBIR: Towards Blind Image Restoration with Generative Diffusion Priorcited by 255
  8. 2022Towards Robust Blind Face Restoration with Codebook Lookup Transformercited by 230
  9. 2023Implicit Diffusion Models for Continuous Super-Resolutioncited by 216
  10. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  11. 2022StyleGAN-Human: A Data-Centric Odyssey of Human Generationcited by 143
  12. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 133
38 more
  1. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  2. 2022Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priorscited by 98
  3. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  4. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 96
  5. 2023DR2: Diffusion-based Robust Degradation Remover for Blind Face Restorationcited by 79
  6. 2023CoSeR: Bridging Image and Language for Cognitive Super-Resolutioncited by 66
  7. 2023Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolutioncited by 59
  8. 2022High-resolution Face Swapping via Latent Semantics Disentanglementcited by 57
  9. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  10. 2025DiT4SR: Taming Diffusion Transformer for Real-World Image Super-Resolutioncited by 50
  11. 2023PGDiff: Guiding Diffusion Models for Versatile Face Restoration via Partial Guidancecited by 49
  12. 2022Deep Equilibrium Approaches to Diffusion Modelscited by 42
  13. 2024XPSR: Cross-modal Priors for Diffusion-based Image Super-Resolutioncited by 41
  14. 2022Learning Dual Memory Dictionaries for Blind Face Restorationcited by 40
  15. 2022GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priorscited by 39
  16. 2022State-of-the-Art in the Architecture, Methods and Applications of StyleGANcited by 34
  17. 2022BigColor: Colorization using a Generative Color Prior for Natural Imagescited by 34
  18. 2024OSDFace: One-Step Diffusion Model for Face Restorationcited by 33
  19. 2021Deep Learning-based Face Super-Resolution: A Surveycited by 32
  20. 2024FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolutioncited by 31
  21. 2022MyStyle: A Personalized Generative Priorcited by 26
  22. 2021Towards Open-World Text-Guided Face Image Generation and Manipulationcited by 25
  23. 2024Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decodercited by 25
  24. 2022Variational Deep Image Restorationcited by 24
  25. 2022Self-Supervised Geometry-Aware Encoder for Style-Based 3D GAN Inversioncited by 24
  26. 2023Learning Generative Structure Prior for Blind Text Image Super-resolutioncited by 24
  27. 2023DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generationcited by 24
  28. 2023Dual Associated Encoder for Face Restorationcited by 23
  29. 2022Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Modelcited by 22
  30. 2022GAN Prior based Null-Space Learning for Consistent Super-Resolutioncited by 22
  31. 2023Image Super-Resolution with Text Prompt Diffusioncited by 22
  32. 2021LTT-GAN: Looking Through Turbulence by Inverting GANscited by 21
  33. 2022Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modelingcited by 20
  34. 2022VToonify: Controllable High-Resolution Portrait Video Style Transfercited by 20
  35. 2022GLEAN: Generative Latent Bank for Image Super-Resolution and Beyondcited by 19
  36. 2023StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Facescited by 19
  37. 2023FABRIC: Personalizing Diffusion Models with Iterative Feedbackcited by 19
  38. 2021Learning for Unconstrained Space-Time Video Super-Resolutioncited by 18

50 most cited of 158 All 158 (JSON)