mlsanityData to 14 Oct 2026

Image Super-Resolution Using Deep Convolutional Networks

arXiv 1501.00092 ↗First posted 31 Dec 2014cs.CV cs.NEcited by 1,224

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Cited by 163 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural network (CNN) that takes the low-resolution image as the input and outputs the high-resolution one. We further show that traditional sparse-coding-based SR methods can also be viewed as a deep convolutional network. But unlike traditional methods that handle each component separately, our method jointly optimizes all layers. Our deep CNN has a lightweight structure, yet demonstrates state-of-the-art restoration quality, and achieves fast speed for practical on-line usage. We explore different network structures and parameter settings to achieve trade-offs between performance and speed. Moreover, we extend our network to cope with three color channels simultaneously, and show better overall reconstruction quality.

Key facts. Cited by 1,224 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Dec 2014.

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Citing papers per year: 2020: 1; 2021: 229; 2022: 241; 2023: 206; 2024: 209; 2025: 215; 2026: 123.

1,224 papers.

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  1. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  2. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 970
  3. 2022Denoising Diffusion Restoration Modelscited by 963
  4. 2021Multi-Stage Progressive Image Restorationcited by 816
  5. 2022Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Modelcited by 583
  6. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  7. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolutioncited by 489
  8. 2022Activating More Pixels in Image Super-Resolution Transformercited by 438
  9. 2021Deep Long-Tailed Learning: A Surveycited by 417
  10. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
  11. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shiftingcited by 365
  12. 2023Denoising Diffusion Models for Plug-and-Play Image Restorationcited by 340
38 more
  1. 2024Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wildcited by 286
  2. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 255
  3. 2023Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylizationcited by 254
  4. 2023SinSR: Diffusion-Based Image Super-Resolution in a Single Stepcited by 238
  5. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancementcited by 199
  6. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 183
  7. 2024A Survey on Diffusion Models for Inverse Problemscited by 180
  8. 2023Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restorationcited by 165
  9. 2022Efficient Long-Range Attention Network for Image Super-resolutioncited by 151
  10. 2021Transformer for Single Image Super-Resolutioncited by 150
  11. 2022Learning Enriched Features for Fast Image Restoration and Enhancementcited by 150
  12. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  13. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 140
  14. 2021Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embeddingcited by 134
  15. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 134
  16. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagerycited by 131
  17. 2023Low-Light Image Enhancement with Wavelet-based Diffusion Modelscited by 127
  18. 2022Deep Generalized Unfolding Networks for Image Restorationcited by 121
  19. 2024FeatUp: A Model-Agnostic Framework for Features at Any Resolutioncited by 116
  20. 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imagingcited by 107
  21. 2021R2RNet: Low-light Image Enhancement via Real-low to Real-normal Networkcited by 106
  22. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 97
  23. 2021NeRF-SR: High-Quality Neural Radiance Fields using Supersamplingcited by 95
  24. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  25. 2024TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolutioncited by 87
  26. 2023Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Modelscited by 86
  27. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  28. 2021Deep Burst Super-Resolutioncited by 83
  29. 2021Equivariant Imaging: Learning Beyond the Range Spacecited by 83
  30. 2021ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristiccited by 81
  31. 2021Intriguing Findings of Frequency Selection for Image Deblurringcited by 81
  32. 2021MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolutioncited by 80
  33. 2022An Introduction to Neural Data Compressioncited by 79
  34. 2021Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyondcited by 76
  35. 2021Convolutional Neural Network Pruning with Structural Redundancy Reductioncited by 73
  36. 2021Fourier Space Losses for Efficient Perceptual Image Super-Resolutioncited by 73
  37. 2022GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifoldscited by 73
  38. 2024Pan-Mamba: Effective pan-sharpening with State Space Modelcited by 73

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