1 citations · 1 across the 2 of their papers we have counts for
3 papers
LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization
Alessio Spagnoletti, Jean Prost, Andrés Almansa +2
Text-to-image latent diffusion models (LDMs) have recently emerged as powerful generative models with great potential for solving inverse problems in imaging. However, leveraging s…
Plug-and-Play image restoration with Stochastic deNOising REgularization
Marien Renaud, Jean Prost, Arthur Leclaire +1
Plug-and-Play (PnP) algorithms are a class of iterative algorithms that address image inverse problems by combining a physical model and a deep neural network for regularization. E…
Diverse super-resolution with pretrained deep hiererarchical VAEs
Jean Prost, Antoine Houdard, Andrés Almansa +1
We investigate the problem of producing diverse solutions to an image super-resolution problem. From a probabilistic perspective, this can be done by sampling from the posterior di…