mlsanityData to 7 Oct 2026

FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

arXiv 1710.04026 ↗First posted 11 Oct 2017cs.CVcited by 509

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Cited by 27 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising. However, these methods mostly learn a specific model for each noise level, and require multiple models for denoising images with different noise levels. They also lack flexibility to deal with spatially variant noise, limiting their applications in practical denoising. To address these issues, we present a fast and flexible denoising convolutional neural network, namely FFDNet, with a tunable noise level map as the input. The proposed FFDNet works on downsampled sub-images, achieving a good trade-off between inference speed and denoising performance. In contrast to the existing discriminative denoisers, FFDNet enjoys several desirable properties, including (i) the ability to handle a wide range of noise levels (i.e., [0, 75]) effectively with a single network, (ii) the ability to remove spatially variant noise by specifying a non-uniform noise level map, and (iii) faster speed than benchmark BM3D even on CPU without sacrificing denoising performance. Extensive experiments on synthetic and real noisy images are conducted to evaluate FFDNet in comparison with state-of-the-art denoisers. The results show that FFDNet is effective and efficient, making it highly attractive for practical denoising applications.

Key facts. Cited by 509 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Oct 2017.

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Citing papers per year: 2020: 1; 2021: 96; 2022: 108; 2023: 109; 2024: 79; 2025: 67; 2026: 49.

509 papers.

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  1. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  2. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  3. 2021Designing a Practical Degradation Model for Deep Blind Image Super-Resolutioncited by 524
  4. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shiftingcited by 360
  5. 2024MambaIR: A Simple Baseline for Image Restoration with State-Space Modelcited by 349
  6. 2023DiffBIR: Towards Blind Image Restoration with Generative Diffusion Priorcited by 255
  7. 2021SNIPS: Solving Noisy Inverse Problems Stochasticallycited by 191
  8. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 182
  9. 2021Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Imagescited by 171
  10. 2022Learning Enriched Features for Fast Image Restoration and Enhancementcited by 150
  11. 2023Efficient and Explicit Modelling of Image Hierarchies for Image Restorationcited by 145
  12. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 139
38 more
  1. 2022Deep Generalized Unfolding Networks for Image Restorationcited by 119
  2. 2022Asymmetric Student-Teacher Networks for Industrial Anomaly Detectioncited by 115
  3. 2023PromptIR: Prompting for All-in-One Blind Image Restorationcited by 113
  4. 2024AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulationcited by 108
  5. 2021Gradient Step Denoiser for convergent Plug-and-Playcited by 107
  6. 2021R2RNet: Low-light Image Enhancement via Real-low to Real-normal Networkcited by 106
  7. 2021Bayesian imaging using Plug & Play priors: when Langevin meets Tweediecited by 96
  8. 2022AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Networkcited by 92
  9. 2022Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesiscited by 85
  10. 2022Accurate Image Restoration with Attention Retractable Transformercited by 85
  11. 2022Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spotscited by 83
  12. 2022Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularizationcited by 79
  13. 2021Towards Flexible Blind JPEG Artifacts Removalcited by 76
  14. 2022Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restorationcited by 72
  15. 2023Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --cited by 71
  16. 2022CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolutioncited by 69
  17. 2021Invertible Denoising Network: A Light Solution for Real Noise Removalcited by 68
  18. 2021On Efficient Transformer-Based Image Pre-training for Low-Level Visioncited by 64
  19. 2023HAT: Hybrid Attention Transformer for Image Restorationcited by 64
  20. 2024Efficient Diffusion Model for Image Restoration by Residual Shiftingcited by 64
  21. 2024DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curationcited by 64
  22. 2021Mobile Computational Photography: A Tourcited by 62
  23. 2021Improving Image Restoration by Revisiting Global Information Aggregationcited by 60
  24. 2024Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restorationcited by 60
  25. 2021HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantizationcited by 58
  26. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  27. 2023Masked Image Training for Generalizable Deep Image Denoisingcited by 57
  28. 2022C2N: Practical Generative Noise Modeling for Real-World Denoisingcited by 56
  29. 2023A Comparative Study of Image Restoration Networks for General Backbone Network Designcited by 56
  30. 2021Adaptive Unfolding Total Variation Network for Low-Light Image Enhancementcited by 55
  31. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  32. 2022Reference-based Image Super-Resolution with Deformable Attention Transformercited by 50
  33. 2021Dynamic Attentive Graph Learning for Image Restorationcited by 48
  34. 2023WaveDM: Wavelet-Based Diffusion Models for Image Restorationcited by 46
  35. 2023Neural Degradation Representation Learning for All-In-One Image Restorationcited by 46
  36. 2021Stochastic Image Denoising by Sampling from the Posterior Distributioncited by 45
  37. 2022CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Imagecited by 45
  38. 2023Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streakscited by 45

50 most cited of 509 All 509 (JSON)