1 code implementation • 1 Feb 2024 • Marien Renaud, Jean Prost, Arthur Leclaire, Nicolas Papadakis
Even if they produce impressive image restoration results, these algorithms rely on a non-standard use of a denoiser on images that are less and less noisy along the iterations, which contrasts with recent algorithms based on Diffusion Models (DM), where the denoiser is applied only on re-noised images.
1 code implementation • ICCV 2023 • Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis
Our experiments show that the proposed PnP-HVAE method is competitive with both SOTA denoiser-based PnP approaches, and other SOTA restoration methods based on generative models.
no code implementations • CVPR 2023 • Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero
In this work, we argue that accounting for shadow deformation is essential when designing a video shadow detection method.
no code implementations • 20 May 2022 • Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis
We investigate the problem of producing diverse solutions to an image super-resolution problem.
no code implementations • 11 Feb 2021 • Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis
In this work, we propose a framework to learn a local regularization model for solving general image restoration problems.