PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization

24 May 2022

Papers citing "PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization"

7 / 7 papers shown

Title
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching Ségolène Martin Anne Gagneux Paul Hagemann Gabriele Steidl 42 9 0 03 Oct 2024
Stability of Data-Dependent Ridge-Regularization for Inverse Problems Sebastian Neumayer Fabian Altekrüger 42 1 0 18 Jun 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 29 6 0 27 Dec 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 29 9 0 28 Mar 2023
Denoising Diffusion Restoration Models Bahjat Kawar Michael Elad Stefano Ermon Jiaming Song DiffM 220 787 0 27 Jan 2022
Posterior Sampling for Image Restoration using Explicit Patch Priors Roy Friedman Yair Weiss 40 5 0 20 Apr 2021
Solving Inverse Problems with a Flow-based Noise Model Jay Whang Qi Lei A. Dimakis 64 36 0 18 Mar 2020