arXiv Computer Vision
Dual Flow: Joint Image-Measurement Flow for Inverse Problems
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Sep 14
Fast and Faithful: Principled Conditional Flow Matching for Inverse Problems
arXiv:2609.12953v1 Announce Type: new Abstract: Flow matching approaches to imaging inverse problems commonly incorporate measurements in two ways. Conditioning-based approaches supply measurement-de...
arXiv AI
Jul 22
Provable diffusion-based posterior sampling for linear inverse problems via DDIM
arXiv:2607. 19333v1 Announce Type: cross Abstract: Diffusion-based methods have achieved remarkable empirical success in solving inverse problems.
arXiv Machine Learning
Jun 16
Exact Posterior Score Estimation for Solving Linear Inverse Problems
arXiv:2606. 17048v1 Announce Type: new Abstract: Diffusion and flow-based models learn powerful data priors by training a denoiser to reverse Gaussian corruption.
arXiv Machine Learning
Oct 8
Twist Flow for Inverse Problems
arXiv:2610. 09281v1 Announce Type: new Abstract: In Bayesian inverse problems, posterior sampling requires generating samples that are consistent with given observations while capturing the range of plausible solutions.
arXiv Computer Vision
4d ago
Retrieval-Augmented Initialization with Dual-Guided Inversion for Flow-Based Inverse Problem Solvers
The paper introduces Retrieval-Augmented Initialization with Dual-Guided Inversion (RA‑DGI), a method that improves the initial noise used by flow‑based inverse problem solvers by leveraging retrieved proxy clean images and dual‑guided inversion. Experiments across multiple inverse problems show that this improved initialization significantly enhances reconstruction fidelity and perceptual performance compared to standard random noise and inference‑time scaling strategies, while adding less computational overhead.
arXiv Computer Vision
Sep 15
Direct Conditional Transition Sampling for Diffusion Inverse Problems
arXiv:2609.14596v1 Announce Type: new Abstract: Training-free diffusion inverse solvers typically choose between local measurement guidance and costly clean-space posterior updates. Independent poste...