All-in-One Image Restoration

Overview

All-in-one image restoration studies how one model can recover images affected by different problems—such as rain, haze, blur, noise, or combinations of them—without needing a separate system for each. Common approaches use degradation-aware prompts or physical priors, specialized experts with routing, and shared CNN or transformer backbones; diffusion and other generative models are also used to reconstruct missing detail. Researchers test these systems on standard task benchmarks and increasingly on real-world, mixed-degradation, and unseen conditions, sometimes measuring downstream performance as well as image quality. A central challenge is balancing specialization with generalization: models must remove artifacts without erasing meaningful content or inventing details, while remaining efficient and controllable.

Latest papers

CardsList

88 papers6 papers in the last four weeks, down 45% on the four weeks before. 0.0% of all new papers.

  1. A Unified Foundation Model for All-in-One Multi-Modal Remote Sensing Image Restoration and Fusion with Language Prompting

    Apr 7, 2026Yongchuan Cui, Peng LiuAll-in-One Image RestorationImage Restoration

  2. Your Pre-trained Diffusion Model Secretly Knows Restoration

    Apr 6, 2026Sudarshan Rajagopalan, Vishal M. PatelDiffusion Models for Image RestorationAll-in-One Image Restoration

  3. DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping

    Apr 3, 2026Soumendu Majee, Joshua Peter Ebenezer, Abhinau K. Venkataramanan +6Image EnhancementImage Restoration

  4. Can Nano Banana 2 Replace Traditional Image Restoration Models? An Evaluation of Its Performance on Image Restoration Tasks

    Apr 3, 2026Weixiong Sun, Xiang Yin, Chao DongImage RestorationAll-in-One Image Restoration

  5. Task-Guided Prompting for Unified Remote Sensing Image Restoration

    Apr 3, 2026Wenli Huang, Yang Wu, Xiaomeng Xin +3All-in-One Image RestorationRemote Sensing

  6. Divide and Restore: A Modular Task-Decoupled Framework for Universal Image Restoration

    Mar 30, 2026Joanna Wiekiera, Martyna ZurImage RestorationAll-in-One Image Restoration

  7. Restore, Assess, Repeat: A Unified Framework for Iterative Image Restoration

    Mar 27, 2026I-Hsiang Chen, Isma Hadji, Enrique Sanchez +5Image RestorationAll-in-One Image Restoration

  8. RealRestorer: Towards Generalizable Real-World Image Restoration with Large-Scale Image Editing Models

    Mar 26, 2026Yufeng Yang, Xianfang Zeng, Zhangqi Jiang +8Image RestorationAll-in-One Image Restoration

  9. PASDiff: Physics-Aware Semantic Guidance for Joint Real-World Low-Light Face Enhancement and Restoration

    Mar 26, 2026Yilin Ni, Wenjie Li, Zhengxue Wang +3Diffusion Model GuidanceLow-Light Image Enhancement

  10. MedQ-UNI: Toward Unified Medical Image Quality Assessment and Restoration via Vision-Language Modeling

    Mar 19, 2026Jiyao Liu, Junzhi Ning, Wanying Qu +4Medical Image Quality AssessmentMedical Image Analysis

  11. Unified Removal of Raindrops and Reflections: A New Benchmark and A Novel Pipeline

    Mar 17, 2026Xingyu Liu, Zewei He, Yu Chen +4Diffusion Models for Image RestorationImage Enhancement

  12. M2IR: Proactive All-in-One Image Restoration via Mamba-style Modulation and Mixture-of-Experts

    Mar 16, 2026Shiwei Wang, Yongzhen Wang, Bingwen Hu +3Degradation-Aware Image RestorationAll-in-One Image Restoration

  13. Seeing Through the PRISM: Compound & Controllable Restoration of Scientific Images

    Mar 14, 2026Rupa Kurinchi-Vendhan, Pratyusha Sharma, Antonio Torralba +1Image RestorationAll-in-One Image Restoration

  14. V-Bridge: Bridging Video Generative Priors to Versatile Few-shot Image Restoration

    Mar 13, 2026Shenghe Zheng, Junpeng Jiang, Wenbo LiImage RestorationAll-in-One Image Restoration

  15. UnSCAR: Universal, Scalable, Controllable, and Adaptable Image Restoration

    Mar 8, 2026Debabrata Mandal, Soumitri Chattopadhyay, Yujie Wang +2All-in-One Image RestorationCatastrophic Forgetting

  16. Physics-Guided VLM Priors for All-Cloud Removal

    Mar 7, 2026Liying Xu, Huifang Li, Huanfeng ShenRemote SensingPhysics-Guided Image Restoration

  17. SLER-IR: Spherical Layer-wise Expert Routing for All-in-One Image Restoration

    Mar 6, 2026Peng Shurui, Xin Lin, Shi Luo +5Image RestorationAll-in-One Image Restoration

  18. All-in-One Image Restoration via Causal-Deconfounding Wavelet-Disentangled Prompt Network

    Mar 4, 2026Bingnan Wang, Bin Qin, Jiangmeng Li +3All-in-One Image RestorationImage Restoration

  19. MiM-DiT: MoE in MoE with Diffusion Transformers for All-in-One Image Restoration

    Mar 3, 2026Lingshun Kong, Jiawei Zhang, Zhengpeng Duan +6All-in-One Image RestorationDiffusion Models for Image Restoration

  20. CAWM-Mamba: A unified model for infrared-visible image fusion and compound adverse weather restoration

    Mar 3, 2026Huichun Liu, Xiaosong Li, Zhuangfan Huang +3Infrared-Visible Image FusionMultimodal Fusion

  21. Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration

    Mar 2, 2026Guanglu Dong, Chunlei Li, Chao Ren +4Image RestorationAll-in-One Image Restoration

  22. Neural Discrimination-Prompted Transformers for Efficient UHD Image Restoration and Enhancement

    Mar 1, 2026Cong Wang, Jinshan Pan, Liyan Wang +2All-in-One Image RestorationEfficient ViTs

  23. Learning Continuous Wasserstein Barycenter Space for Generalized All-in-One Image Restoration

    Feb 26, 2026Xiaole Tang, Xiaoyi He, Jiayi Xu +2All-in-One Image RestorationOOD Generalization

  24. TPGDiff: Hierarchical Triple-Prior Guided Diffusion for Image Restoration

    Jan 28, 2026Yanjie Tu, Qingsen Yan, Axi Niu +1Geometry-Guided Image RestorationImage Restoration

  25. Rectification Reimagined: A Unified Mamba Model for Image Correction and Rectangling with Prompts

    Dec 21, 2025Linwei Qiu, Gongzhe Li, Xiaozhe Zhang +2All-in-One Image Restoration

  26. ClusIR: Towards Cluster-Guided All-in-One Image Restoration

    Dec 11, 2025Shengkai Hu, Jiaqi Ma, Xu Zhang +3Mixture of ExpertsAll-in-One Image Restoration