2 citations · 5 across the 8 of their papers we have counts for
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DeepInverse: A Python package for solving imaging inverse problems with deep learning
Julián Tachella, Matthieu Terris, Samuel Hurault +24
DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems. The library covers all crucial steps in image reconstruction from the efficient implementa…
Reconstruct Anything Model: a lightweight general model for computational imaging
Matthieu Terris, Samuel Hurault, Maxime Song +1
Most existing learning-based methods for solving imaging inverse problems can be roughly divided into two classes: iterative algorithms, such as plug-and-play and diffusion methods…
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
Samuel Hurault, Ulugbek Kamilov, Arthur Leclaire +1
Plug-and-Play (PnP) methods are efficient iterative algorithms for solving ill-posed image inverse problems. PnP methods are obtained by using deep Gaussian denoisers instead of th…