mlsanityData to 14 Oct 2026

A Comparative Study of Image Restoration Networks for General Backbone Network Design

arXiv 2310.11881 ↗First posted 18 Oct 2023cs.CVcited by 57

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Abstract (arXiv)

Despite the significant progress made by deep models in various image restoration tasks, existing image restoration networks still face challenges in terms of task generality. An intuitive manifestation is that networks which excel in certain tasks often fail to deliver satisfactory results in others. To illustrate this point, we select five representative networks and conduct a comparative study on five classic image restoration tasks. First, we provide a detailed explanation of the characteristics of different image restoration tasks and backbone networks. Following this, we present the benchmark results and analyze the reasons behind the performance disparity of different models across various tasks. Drawing from this comparative study, we propose that a general image restoration backbone network needs to meet the functional requirements of diverse tasks. Based on this principle, we design a new general image restoration backbone network, X-Restormer. Extensive experiments demonstrate that X-Restormer possesses good task generality and achieves state-of-the-art performance across a variety of tasks.

Key facts. Cited by 57 papers in the map (data through 14 Oct 2026). Builds on 45 of its 61 references that are in the map. First posted on arXiv 18 Oct 2023.

Builds on

45 of 61 references.

References · 45

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  3. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  4. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,627
  5. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,552
  6. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,358
  7. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,264
  8. 2020Pre-Trained Image Processing Transformercited by 893
  9. 2021Uformer: A General U-Shaped Transformer for Image Restorationcited by 866
  10. 2021Multi-Stage Progressive Image Restorationcited by 816
  11. 2018Residual Dense Network for Image Super-Resolutioncited by 799
  12. 2016Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurringcited by 727
33 more
  1. 2022Simple Baselines for Image Restorationcited by 708
  2. 2017FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoisingcited by 510
  3. 2020Plug-and-Play Image Restoration with Deep Denoiser Priorcited by 470
  4. 2017Benchmarking Single Image Dehazing and Beyondcited by 447
  5. 2022Activating More Pixels in Image Super-Resolution Transformercited by 438
  6. 2017Learning Deep CNN Denoiser Prior for Image Restorationcited by 408
  7. 2016Deep Joint Rain Detection and Removal from a Single Imagecited by 352
  8. 2015Sketch-based Manga Retrieval using Manga109 Datasetcited by 329
  9. 2021Rethinking Coarse-to-Fine Approach in Single Image Deblurringcited by 326
  10. 2016DehazeNet: An End-to-End System for Single Image Haze Removalcited by 314
  11. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 302
  12. 2019Progressive Image Deraining Networks: A Better and Simpler Baselinecited by 272
  13. 2020Single Image Super-Resolution via a Holistic Attention Networkcited by 265
  14. 2020Multi-Scale Progressive Fusion Network for Single Image Derainingcited by 260
  15. 2022Vision Transformers for Single Image Dehazingcited by 260
  16. 2018Density-aware Single Image De-raining using a Multi-stream Dense Networkcited by 248
  17. 2021HINet: Half Instance Normalization Network for Image Restorationcited by 237
  18. 2019Residual Non-local Attention Networks for Image Restorationcited by 236
  19. 2021Contrastive Learning for Compact Single Image Dehazingcited by 219
  20. 2018Multi-level Wavelet-CNN for Image Restorationcited by 184
  21. 2018Residual Dense Network for Image Restorationcited by 181
  22. 2020Human-Aware Motion Deblurringcited by 175
  23. 2020Defocus Deblurring Using Dual-Pixel Datacited by 139
  24. 2021CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attentioncited by 139
  25. 2020Interpreting Super-Resolution Networks with Local Attribution Mapscited by 136
  26. 2023Dual Aggregation Transformer for Image Super-Resolutioncited by 124
  27. 2022Accurate Image Restoration with Attention Retractable Transformercited by 85
  28. 2021Spatially-Adaptive Image Restoration using Distortion-Guided Networkscited by 77
  29. 2023HAT: Hybrid Attention Transformer for Image Restorationcited by 66
  30. 2021On Efficient Transformer-Based Image Pre-training for Low-Level Visioncited by 64
  31. 2021Improving Image Restoration by Revisiting Global Information Aggregationcited by 61
  32. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 55
  33. 2022Revisiting RCAN: Improved Training for Image Super-Resolutioncited by 32

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 15; 2025: 20; 2026: 20.

57 papers.

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  1. 2023Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Modelscited by 105
  2. 2024MambaIRv2: Attentive State Space Restorationcited by 94
  3. 2024Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restorationcited by 62
  4. 2024An Intelligent Agentic System for Complex Image Restoration Problemscited by 43
  5. 2024FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restorationcited by 39
  6. 2024Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Datasetcited by 38
  7. 2025NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Resultscited by 22
  8. 2025Multi-Agent Image Restorationcited by 21
  9. 2024Learning A Low-Level Vision Generalist via Visual Task Promptcited by 18
  10. 2025Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Visioncited by 14
  11. 2024High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformercited by 12
  12. 2025NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolutioncited by 9
38 more
  1. 2025FoundIR-v2: Optimizing Pre-Training Data Mixtures for Image Restoration Foundation Modelcited by 9
  2. 2023Learning to See Low-Light Images via Feature Domain Adaptationcited by 8
  3. 2024Interpreting Low-level Vision Models with Causal Effect Mapscited by 8
  4. 2024PromptHSI: Universal Hyperspectral Image Restoration with Vision-Language Modulated Frequency Adaptationcited by 7
  5. 2025DSwinIR: Rethinking Window-based Attention for Image Restorationcited by 7
  6. 2024A Preliminary Exploration Towards General Image Restorationcited by 6
  7. 2025Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedbackcited by 6
  8. 2025NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challengecited by 5
  9. 2026TIR-Agent: Training an Explorative and Efficient Agent for Image Restorationcited by 5
  10. 2024Bracketing Image Restoration and Enhancement with High-Low Frequency Decompositioncited by 4
  11. 2024ShadowHack: Hacking Shadows via Luminance-Color Divide and Conquercited by 4
  12. 2025Exploring Scalable Unified Modeling for General Low-Level Visioncited by 4
  13. 2026TPGDiff: Hierarchical Triple-Prior Guided Diffusion for Image Restorationcited by 4
  14. 2026OPERA: An Agent for Image Restoration with End-to-End Joint Planning-Execution Optimizationcited by 4
  15. 2026Self-Evolving Agentic Image Restoration via Deliberate Planning and Intuitive Executioncited by 4
  16. 2024Adaptive Blind All-in-One Image Restorationcited by 3
  17. 2025Elucidating and Endowing the Diffusion Training Paradigm for General Image Restorationcited by 3
  18. 2025Global Modeling Matters: A Fast, Lightweight and Effective Baseline for Efficient Image Restorationcited by 3
  19. 2025Enhancing Infrared Vision: Progressive Prompt Fusion Network and Benchmarkcited by 3
  20. 2026V-Bridge: Bridging Video Generative Priors to Versatile Few-shot Image Restorationcited by 3
  21. 2025Omni-Weather: A Unified Multimodal Model for Weather Radar Understanding and Generationcited by 2
  22. 2026ShiftLUT: Spatial Shift Enhanced Look-Up Tables for Efficient Image Restorationcited by 2
  23. 2024Aberration Correcting Vision Transformers for High-Fidelity Metalens Imagingcited by 1
  24. 2024Towards Context-aware Convolutional Network for Image Restorationcited by 1
  25. 2025Distilling Textual Priors from LLM to Efficient Image Fusioncited by 1
  26. 2025A Preliminary Study on GPT-Image Generation Model for Image Restorationcited by 1
  27. 2025Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priorscited by 1
  28. 2026Position: Evaluation of Visual Processing Should Be Human-Centered, Not Metric-Centeredcited by 1
  29. 2026GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restorationcited by 1
  30. 2026The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Resultscited by 1
  31. 2026SkillIR: Evolving Scene-Aware Skills for Agentic Image Restorationcited by 1
  32. 2025One Latent Space to Rule All Degradations: Unifying Restoration Knowledge for Image Fusioncited by 0
  33. 2025Image Restoration via Multi-domain Learningcited by 0
  34. 2025Benchmarking Endoscopic Surgical Image Restoration and Beyondcited by 0
  35. 2025Not All Degradations Are Equal: A Targeted Feature Denoising Framework for Generalizable Image Super-Resolutioncited by 0
  36. 2026Efficient Deep Demosaicing with Spatially Downsampled Isotropic Networkscited by 0
  37. 2026Revisiting Global Token Mixing in Task-Dependent MRI Restoration: Insights from Minimal Gated CNN Baselinescited by 0
  38. 2026VQ-Jarvis: Retrieval-Augmented Video Restoration Agent with Sharp Vision and Fast Thoughtcited by 0

50 most cited of 57 All 57 (JSON)