Diffusion Models for Image Restoration

Follow this topic Ask about this topic

Momentum

6 papers in the last four weeks, down 33% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 115

All topics

Sparse-to-Complete: From Sparse Image Captures to Complete 3D Scenes
May 7, 2026Yiyang Shen, Yin Yang, Kun Zhou +13D Gaussian Splatting Diffusion Models for Image Restoration
State Key Lab of CAD&CG, Zhejiang University, China · University of Utah, USA · State Key Lab of CAD&CG, Zhejiang University, China and Hangzhou Research Institute of Holographic and AI Technology, China +1
Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees
May 6, 2026Ahmad Aghapour, Erhan Bayraktar, Asaf CohenDiffusion Models for Image Restoration Langevin Dynamics
Department of Mathematics University of Michigan Ann Arbor, MI 48109, USA
Faithful Extreme Image Rescaling with Learnable Reversible Transformation and Semantic Priors
May 1, 2026Hao Wei, Yanhui Zhou, Chenyang Ge +2Diffusion Models for Image Restoration Image Restoration
State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University · School of Information and Communications Engineering, Xi’an Jiaotong University · Department of Computer Science and Software Engineering, The University of Western Australia
GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution
Apr 28, 2026Fabio D'Oronzio, Federico Putamorsi, Leonardo Zini +2Diffusion Models for Image Restoration Diffusion Model Fine-Tuning
University of Modena and Reggio Emilia, Italy
Edge-Cloud Collaborative Reconstruction via Structure-Aware Latent Diffusion for Downstream Remote Sensing Perception
Apr 28, 2026Yun Li, Xianju LiDiffusion Models for Image Restoration Edge Computing
School of Computer Science, China University of Geosciences, Wuhan, Hubei, China.
Bridging Restoration and Generation Manifolds in One-Step Diffusion for Real-World Super-Resolution
Apr 27, 2026Shyang-En Weng, Yi-Cheng Liao, Yu-Syuan Xu +2Diffusion Model Inversion Diffusion Models for Image Restoration
National Yang Ming Chiao Tung University, Hsinchu, Taiwan · MediaTek Inc., Taiwan
ZID-Net: Zero-Inference Diffusion Prior Decoupling Network for Single Image Dehazing
Apr 26, 2026Xinheng Li, Minghao Chen, Mengqing Wu +2Diffusion Models for Image Restoration Diffusion Model Distillation
College of Information Science and Engineering, Hohai University, Changzhou, 213200, Jiangsu, China
BurstGP: Enhancing Raw Burst Image Super Resolution with Generative Priors
Apr 26, 2026Dong Huo, Tristan Aumentado-Armstrong, Samrudhdhi B. Rangrej +8Diffusion Models for Image Restoration Image Super-Resolution
AI Center - Toronto, Samsung Electronics · University of Toronto · Vector Institute +2
Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data
Apr 24, 2026Harry Dong, Timofey Efimov, Megna Shah +4Diffusion Models for Image Restoration Materials Science
Department of Electrical and Computer Engineering, Carnegie Mellon University, USA · Materials and Manufacturing Directorate, Air Force Research Laboratory, USA · Department of Materials Science and Engineering, Carnegie Mellon University, USA +1
DiffNR: Diffusion-Enhanced Neural Representation Optimization for Sparse-View 3D Tomographic Reconstruction
Apr 23, 2026Shiyan Su, Ruyi Zha, Danli Shi +2Diffusion Models for Image Restoration Sparse-View CT Reconstruction
1Monash University · 2The Australian National University · 3Hong Kong Polytechnic University
Diffusion Autoencoder for Unsupervised Artifact Restoration in Handheld Fundus Images
Apr 17, 2026Mathumetha Palani, Kavya Puthumana, Ayantika Das +1Diffusion Models for Image Restoration Medical Imaging
Nuvo AI, Chennai, India · Indian Institute of Technology Madras, India
FUMO: Prior-Modulated Diffusion for Single Image Reflection Removal
Mar 19, 2026Telang Xu, Chaoyang Zhang, Guangtao Zhai +1Diffusion Models for Image Restoration Image Restoration
Shanghai Jiao Tong University, Shanghai, China · Shanghai Innovation Institute, Shanghai, China · Xi’an Jiaotong University, Xi’an, China
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 Restoration Image Enhancement
Huanjiang Laboratory, Zhuji, China · School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, China · Hangzhou Institute of Technology, Xidian University, Hangzhou, China +1
Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion
Mar 5, 2026Zahra Karimaghaloo, Dumitru Fetco, Haz-Edine Assemlal +2Diffusion Models for Image Restoration Diffusion Model Guidance
Clario part of Thermofisher Scientific, Montreal, Canada · Concordia University, Montreal, Canada
Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration
Jan 27, 2026Zhengjian Yao, Jiakui Hu, Kaiwen Li +5Diffusion Model Alignment Diffusion Models for Image Restoration
Biomedical Engineering Department, College of Future Technology, Peking University, Beijing, China
HaineiFRDM: Structure-Preserving Diffusion for Film Restoration under Fast Motion and Diverse Defects
Dec 31, 2025Rongji Xun, Junjie Yuan, Zhongjie WangDiffusion Models for Image Restoration Image Restoration
Tongji University, Shanghai, China · Shanghai Film Restoration Laboratory, Shanghai, China
GMODiff: One-Step Gain Map Refinement with Diffusion Priors for HDR Reconstruction
Dec 18, 2025Tao Hu, Weiyu Zhou, Yanjie Tu +4Diffusion Models for Image Restoration Latent Diffusion Models
Northwestern Polytechnical University, Xi’an 710072, China · Xi’an University of Architecture and Technology, Xi’an 710055, China · The Shenzhen Research Institute of Northwestern Polytechnical University, Shenzhen 518057, China
DAPS++: Rethinking Diffusion Inverse Problems with Decoupled Posterior Annealing
Nov 21, 2025Hao Chen, Renzheng Zhang, Scott S. HowardDiffusion Models for Image Restoration Bayesian Inverse Problems
University of Notre Dame, Notre Dame, IN 46556, USA
Iterative Diffusion-Refined Neural Attenuation Fields for Multi-Source Stationary CT Reconstruction: NAF Meets Diffusion Model
Nov 18, 2025Jiancheng Fang, Shaoyu Wang, Junlin Wang +3Diffusion Models for Image Restoration Sparse-View CT Reconstruction
School of Information Engineering, Nanchang University, Nanchang 330031, China
BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNet
Nov 17, 2025Min Gu Kwak, Yeonju Lee, Hairong Wang +2Diffusion Models for Image Restoration Medical Image Synthesis
Department of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA · H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA,2026 USA · Operations Research and Industrial Engineering, Cockrell School of Engineering, University of Texas at Austin, Austin, TX, USAJul +2
CharDiff-LP: A Diffusion Model with Character-Level Guidance for License Plate Image Restoration
Oct 20, 2025Kihyun Na, Gyuhwan Park, Injung KimDiffusion Models for Image Restoration Diffusion Model Guidance
Department of Computer Science and Electrical Engineering, General Graduate School, Handong Global University, Pohang 37554, Republic of Korea
TinySR: Pruning Diffusion for Real-World Image Super-Resolution
Aug 24, 2025Linwei Dong, Qingnan Fan, Yuhang Yu +4Diffusion Models for Image Restoration Diffusion Model Inference Acceleration
Zhejiang University · Vivo Mobile Communication Co. Ltd · Zhejiang Lab
FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising
Aug 24, 2025Zhihao Chen, Qi Gao, Zilong Li +4Diffusion Models for Image Restoration Medical Imaging Foundation Models
Institute of Science and Technology for Brain-inspired Intelligence and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China · Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai 200433, China · School of Cyber Science and Engineering, Sichuan University, Chengdu, Sichuan 610065, China +1
EquiReg: Equivariance Regularized Diffusion for Inverse Problems
May 29, 2025Bahareh Tolooshams, Aditi Chandrashekar, Rayhan Zirvi +4Diffusion Models for Image Restoration Diffusion-Based Inverse Problems
University of Alberta · Alberta Machine, Intelligence Institute (Amii) · Neuroscience and Mental Health Institute, University of Alberta +3
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision
Date pendingYuandong Pu, Le Zhuo, Kaiwen Zhu +7Diffusion Models for Image Restoration Image Enhancement
Shanghai Jiao Tong University · Shanghai AI Laboratory · University of Macau +3

May 7, 2026, cs.CVJ/K move · Enter open · S save

Sparse-to-Complete: From Sparse Image Captures to Complete 3D Scenes

Yiyang Shen, Yin Yang, Kun Zhou, Tianjia Shao

State Key Lab of CAD&CG, Zhejiang University, China · University of Utah, USA · State Key Lab of CAD&CG, Zhejiang University, China and Hangzhou Research Institute of Holographic and AI Technology, China+1

3D Gaussian Splatting Diffusion Models for Image Restoration Sparse-View 3D Reconstruction

Open paper AskPDF arXiv

We introduce S2C-3D, a novel sparse-view 3D reconstruction framework for high-fidelity and complete scene reconstruction from as few as six to eight images. Our framework features three components: a specialized diffusion model for scene-specific image restoration, a training-free view-consistency conditioned sampling process in the diffusion model for refined Gaussian optimization, and a camera trajectory planning scheme to ensure comprehensive scene coverage. The specialized diffusion model is developed by finetuning a pretrained architecture on the input views and their corresponding degraded counterparts. The adaptation to the scene distribution allows the model to repair Gaussian renderings while effectively eliminating domain gaps. Meanwhile, the trajectory planning scheme optimizes scene coverage by connecting each newly sampled camera to its two nearest neighbors. By iteratively constructing paths and retaining only those that significantly enhance visibility, the scheme establishes a trajectory that covers the entire scene. To address multi-view conflicts, the view-consistency conditioned sampling process quantifies the consistency between neighboring repaired images. This information is injected as a condition into the sampling process of the frozen diffusion model, facilitating the generation of view-consistent images without additional training. Consequently, our approach produces high-fidelity 3D Gaussians that are robust to artifacts. Experimental results demonstrate that S2C-3D outperforms state-of-the-art methods, constructing high-quality scenes that are free from missing regions, blurring, or other artifacts with very sparse inputs. The source code and data are available at https://gapszju.github.io/S2C-3D.

Momentum

Related topics

Latest papers 115