Diffusion-Based Inverse Problems

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15 papers in the last four weeks, up 400% on the four weeks before. 0.1% of all new papers.

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ScaleResfusion: Residual Rectified Flow based on Residual Vector Field
Jul 28, 2026Zhenning Shi, Chen Xu, Junhao Zhang +4Diffusion Models for Image Restoration Rectified Flow
College of Computer Science, Nankai University, Tianjin, China · Faculty of Information Science and Computing, University of Macau, Macau, China · CSIRO Data61, Australia +1
SlerpFlow: Spherical Trajectory Correction for Rectified Flow Inversion
Jul 23, 2026Wenbin Duan, Yan Shu, Zhuoyuan Fu +4Diffusion Model Inversion Rectified Flow
University of International Relations, Beijing, China · University of Trento, Trento, Italy · Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China.
$γ$ -Bridge: A Look-Parametric Diffusion Bridge
Jul 21, 2026Xuran Hu, Yujie Zhu, Tengxi Wang +2Diffusion Models for Image Restoration Physics-Guided Image Restoration
Urban Governance and Design Thrust, Society Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · Faculty of Science and Engineering, Macquarie University, NSW 2109, Sydney, Australia · School of Geography and Planning, Ningxia University, Yinchuan, China
Provable diffusion-based posterior sampling for linear inverse problems via DDIM
Jul 21, 2026Yuchen Jiao, Na Li, Changxiao Cai +2Diffusion Models for Image Restoration Bayesian Inverse Problems
Department of Statistics and Data Science, Chinese University of Hong Kong, Hong Kong · Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA · Department of Statistics and Data Science, the Wharton School, University of Pennsylvania, PA, USA
Feature-Guided Diffusion for Non-Differentiable Inverse Rendering
Jul 19, 2026Andrei-Timotei Ardelean, Michael Fischer, Tim Weyrich +1Inverse Rendering Black-Box Optimization
Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany · Adobe Research, London, United Kingdom · Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic
Compression Asymmetry and Trajectory Binding in Noise-Anchored Diffusion Inversion
Jul 8, 2026Yongseong Park, Joeun Kim, HoEun Kim +1Diffusion Model Inversion Diffusion-Based Inverse Problems
Department of EECS DGIST Daegu, Republic of Korea · Department of AI DGIST Daegu, Republic of Korea
When Does High-CFG Diffusion Inversion Fail? A Controlled Study of Prompt--Latent Interactions
Jul 6, 2026Yan Zeng, Yusuke Hosoya, Huyen T. T. Tran +1Diffusion Model Inversion Classifier-Free Guidance
GSIS Tohoku University Sendai, Japan · RIKEN AIP JAPAN
Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models
Jul 3, 2026Ron Levi, Michael EladDiffusion Models for Image Restoration Diffusion-Based Inverse Problems
Department of Computer Science Technion, Israel
High-dimensional Embedding Prior for Noisy K-space Domain MRIReconstruction
Jul 1, 2026Yu Guan, Tianjia Huang, Qinrong Cai +3Diffusion Models for Image Restoration Accelerated MRI Reconstruction
Diffusion-Based Material Regularization for Physics-Based Inverse Rendering
Jun 30, 2026Jingwang Ling, Lifan Wu, Feng Xu +1Inverse Rendering Diffusion-Based Inverse Problems
University of Illinois Urbana-Champaign · NVIDIA · BNRist and School of Software, Tsinghua University
Stochastic Optimal Control Sampling for Diffusion Inverse Problems
Jun 27, 2026Jie Zhang, Youmei Qiu, Hanling Tian +3Stochastic Optimal Control Diffusion-Based Inverse Problems
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China · Shanghai Key Laboratory of Flexible Medical Robotics, Tongren Hospital, Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems
Jun 25, 2026Yuanzhe Wang, Alexandre M. TartakovskyLatent Diffusion Models Bayesian Inverse Problems
Department of Civil and Environmental Engineering University of Illinois Urbana-Champaign Urbana, IL 61801
Exact Posterior Score Estimation for Solving Linear Inverse Problems
Jun 15, 2026Abbas Mammadov, Ozgur Kara, Kaan Oktay +5Diffusion Models for Image Restoration Diffusion-Based Inverse Problems
University of Oxford · UIUC · fal +1
Decoupled Latent Optimization of Diffusion Models for Full Waveform Inversion
Jun 12, 2026Chen Min, Zheng MaDiffusion-Based Inverse Problems PDE Inverse Problems
School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China · CMA-Shanghai, Shanghai Jiao Tong University, Shanghai, China
A Stabilized Path-Space Approach to Diffusion-Based Posterior Sampling
Jun 10, 2026Evan Scope Crafts, Umberto Villa, Saviz Mowlavi +3Bayesian Inverse Problems Diffusion-Based Inverse Problems
Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX · Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX · Mitsubishi Electric Research Laboratories, Cambridge, MA
The Right Measure for Physics-Constrained Generation: A Co-Area Correction for Posterior-Consistent PDE Inverse Problems
Jun 3, 2026Jian Xu, Yanning Wu, Delu Zeng +2Constrained Generative Modeling Physics-Informed Generative Modeling
1RIKEN iTHEMS · 2RIKEN AIP · 3South China University of Technology +1
Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations
Jun 2, 2026Niccolò Perrone, Fanny Lehmann, Stefania Fresca +1PDE Surrogate Modeling Spectral Bias
Université Paris-Saclay, CentraleSupélec, CNRS, ENS Paris-Saclay · Laboratoire de Mécanique Paris-Saclay UMR 9026 · 8-10 rue Joliot Curie, 91190 Gif-sur-Yvette, France +5
RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Construction
Jun 2, 2026Zixuan Guo, Xiucheng Wang, Nan ChengFew-Step Diffusion Sampling Wireless Communications
School of Physics, Xidian University, Xi’an, 710071, China · State Key Laboratory of ISN and School of Telecommunications Engineering, Xidian University, Xi’an, 710071, China
Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates
Jun 1, 2026Pengfei Jin, Yiqi Tian, Kailong Fan +2Diffusion-Based Inverse Problems Hallucination Mitigation
Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 · Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA 15261
KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems
May 29, 2026Alireza Kheirandish, Jihoon Hong, Sara Fridovich-KeilDiffusion-Based OOD Detection Distribution Shift Detection
Georgia Institute of Technology
When, why, and how do diffusion posterior samplers fail? A finite-sample lens
May 28, 2026Benjamin A. Burns, Sara Fridovich-KeilBayesian Inverse Problems Posterior Sampling
Georgia Institute of Technology
Trajectory Constraints for Imaging Inverse Problems
May 27, 2026Chaoyan Huang, Haijie Yuan, Saiprasad RavishankarImage Reconstruction Computational Imaging
Department of Computational Mathematics, Science, & Engineering, Michigan State University · Department of Electrical Engineering and Computer Science, University of Michigan · Department of Biomedical Engineering, Michigan State University
Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
May 27, 2026Jiawei Zhang, Ziyuan Liu, Leon Yan +2Bayesian Inverse Problems Diffusion-Based Inverse Problems
Department of Electronic Engineering, Tsinghua University, Beijing, China · Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Geometry-Correct Diffusion Posterior Sampling with Denoiser-Pullback Curvature Guidance and Manifold-Aligned Damping
May 27, 2026Seunghyeok Shin, Minwoo Kim, Dabin Kim +1Gauss-Newton Optimization Bayesian Inverse Problems
Department of Electrical and Computer Engineering, Inha University, Incheon, 22212, South Korea.
Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
May 26, 2026Junseo Bang, Dong Ju Mun, Hoigi Seo +2Diffusion Model Guidance Diffusion Timestep Scheduling
Dept. of Electrical and Computer Engineering · INMC · IPAI & AIIS
Unbiased Diffusion Variational Inversion via Principled Posterior Matching
May 24, 2026Weimin Bai, Yuxuan Gu, Yifei Wang +2Diffusion Model Inversion Bayesian Inverse Problems
Peking University
Hierarchical Variational Policies for Reward-Guided Diffusion
May 20, 2026Kushagra Pandey, Farrin Marouf Sofian, Jan Niklas Groeneveld +2Diffusion Models for Image Restoration Diffusion Model Guidance
Department of Computer Science University of California Irvine
Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography
May 19, 2026Giovanni S. Alberti, Damiana Lazzaro, Serena Morigi +2Image Reconstruction Diffusion-Based Inverse Problems
MaLGa Center, Department of Mathematics, University of Genova, Italy · Department of Mathematics, University of Bologna, Bologna, Italy · Department of Mathematics, Harbin Institute of Technology, China
Learning Normalized Energy Models for Linear Inverse Problems
May 15, 2026Nicolas Zilberstein, Santiago Segarra, Eero Simoncelli +1Bayesian Inverse Problems Energy-Based Models
Rice University, Houston, TX, USA · Flatiron Institute, New York, NY, USA · New York University, New York, NY, USA
Image Restoration via Diffusion Models with Dynamic Resolution
May 14, 2026Yang Zheng, Wen Li, Zhaoqiang LiuDiffusion Models for Image Restoration Diffusion-Based Inverse Problems
School of Computer Science and Engineering, University of Electronic Science and Technology of China.

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ScaleResfusion: Residual Rectified Flow based on Residual Vector Field

Zhenning Shi, Chen Xu, Junhao Zhang, Kefei Zhang+3

College of Computer Science, Nankai University, Tianjin, China · Faculty of Information Science and Computing, University of Macau, Macau, China · CSIRO Data61, Australia+1

Diffusion Models for Image Restoration Rectified Flow Diffusion Model Fine-Tuning Diffusion-Based Inverse Problems Image Super-Resolution

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Real-world Image Restoration (Real-IR) aims to recover high-quality (HQ) images from complex and unknown degradations. Recent diffusion-based methods have substantially improved perceptual quality, yet two obstacles remain: methods that sample from Gaussian noise require many steps and are often less faithful to the degraded input, whereas residual-based methods that start from the low-quality (LQ) image typically train task-specific models from scratch, with optimization objectives coupled to a particular noise scheduler, and therefore cannot reuse modern pre-trained generative priors. We present \textbf{ScaleResfusion}, which rewrites residual restoration as a scheduler-independent adaptation interface for pre-trained text-to-image rectified-flow models. Its core, \textbf{Residual Rectified Flow} (RRF), inserts the residual term

R

into the linear transport path of Rectified Flow, so that sampling starts from noisy LQ at an exact acceleration point, where the signal-to-noise ratio of the starting state is continuously controlled by the residual ratio

γ

. The resulting optimization target, the \textbf{residual vector field}, contains no scheduler-specific coefficients and differs from the pre-trained rectified-flow target only by the residual offset

γR

; adapting a frozen billion-scale backbone therefore reduces to fitting this compact residual correction with LoRA-only training. A knowledge-distillation pipeline built around RRF further reduces sampling to as few as 4 steps. Experiments on real-world super-resolution across multiple benchmarks show that ScaleResfusion achieves state-of-the-art restoration quality and transfers consistently across pre-trained rectified-flow backbones from 2B to 9B parameters.

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