mlsanityData to 7 Oct 2026

NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results

arXiv 2005.01996 ↗First posted 5 May 2020eess.IV cs.CVcited by 83

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Abstract (arXiv)

This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are unavailable. For training, only one set of source input images is therefore provided along with a set of unpaired high-quality target images. In Track 1: Image Processing artifacts, the aim is to super-resolve images with synthetically generated image processing artifacts. This allows for quantitative benchmarking of the approaches wrt a ground-truth image. In Track 2: Smartphone Images, real low-quality smart phone images have to be super-resolved. In both tracks, the ultimate goal is to achieve the best perceptual quality, evaluated using a human study. This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019. In total 22 teams competed in the final testing phase, demonstrating new and innovative solutions to the problem.

Key facts. Cited by 83 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 May 2020.

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Citing papers per year: 2021: 26; 2022: 31; 2023: 9; 2024: 13; 2025: 4.

83 papers.

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  1. 2021Designing a Practical Degradation Model for Deep Blind Image Super-Resolutioncited by 524
  2. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
  3. 2022Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolutioncited by 96
  4. 2021Blind Image Super-Resolution: A Survey and Beyondcited by 93
  5. 2024VmambaIR: Visual State Space Model for Image Restorationcited by 90
  6. 2021Deep Burst Super-Resolutioncited by 83
  7. 2021Fourier Space Losses for Efficient Perceptual Image Super-Resolutioncited by 72
  8. 2022Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restorationcited by 72
  9. 2021Real-World Single Image Super-Resolution: A Brief Reviewcited by 65
  10. 2024Towards Realistic Data Generation for Real-World Super-Resolutioncited by 56
  11. 2022Reference-based Image Super-Resolution with Deformable Attention Transformercited by 50
  12. 2023DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Modelscited by 41
38 more
  1. 2021Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Reportcited by 34
  2. 2021Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Reportcited by 34
  3. 2022Neural Optimal Transport with General Cost Functionalscited by 34
  4. 2021DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flowscited by 30
  5. 2022Knowledge Distillation based Degradation Estimation for Blind Super-Resolutioncited by 28
  6. 2022Learning the Degradation Distribution for Blind Image Super-Resolutioncited by 27
  7. 2024Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolutioncited by 25
  8. 2021Optimal Transport for Unsupervised Denoising Learningcited by 24
  9. 2023DiffI2I: Efficient Diffusion Model for Image-to-Image Translationcited by 24
  10. 2022AnimeSR: Learning Real-World Super-Resolution Models for Animation Videoscited by 23
  11. 2021Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Burstscited by 21
  12. 2022Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advancescited by 21
  13. 2021Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Reportcited by 19
  14. 2021Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Reportcited by 19
  15. 2022Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observationscited by 19
  16. 2022Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Datasetcited by 19
  17. 2022Learn from Unpaired Data for Image Restoration: A Variational Bayes Approachcited by 18
  18. 2022Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Reportcited by 16
  19. 2021Toward Interactive Modulation for Photo-Realistic Image Restorationcited by 15
  20. 2021Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Reportcited by 15
  21. 2022Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Reportcited by 13
  22. 2022MicroISP: Processing 32MP Photos on Mobile Devices with Deep Learningcited by 13
  23. 2021Real-World Super-Resolution of Face-Images from Surveillance Camerascited by 11
  24. 2022Generative Adversarial Networks for Image Super-Resolution: A Surveycited by 11
  25. 2022Meta-Learning based Degradation Representation for Blind Super-Resolutioncited by 11
  26. 2021Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Reportcited by 10
  27. 2021Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolutioncited by 10
  28. 2022Real-World Image Super-Resolution by Exclusionary Dual-Learningcited by 10
  29. 2021Generalized Real-World Super-Resolution through Adversarial Robustnesscited by 9
  30. 2022Flexible Style Image Super-Resolution using Conditional Objectivecited by 9
  31. 2023Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 imagescited by 9
  32. 2022Criteria Comparative Learning for Real-scene Image Super-Resolutioncited by 8
  33. 2023End-to-end Alternating Optimization for Real-World Blind Super Resolutioncited by 8
  34. 2021Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstructioncited by 7
  35. 2022Degradation-Guided Meta-Restoration Network for Blind Super-Resolutioncited by 7
  36. 2022PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networkscited by 7
  37. 2023The Perception-Robustness Tradeoff in Deterministic Image Restorationcited by 7
  38. 2021DSRGAN: Detail Prior-Assisted Perceptual Single Image Super-Resolution via Generative Adversarial Networkscited by 6

50 most cited of 83 All 83 (JSON)