Matias Tassano — accepted AI-conference papers

2023

Provably Convergent Plug & Play Linearized ADMM, Applied to Deblurring Spatially Varying Kernels

Charles Laroche, Andrés Almansa, Eva Coupeté, Matias Tassano

ICASSP 2023accepted

Plug & Play methods combine proximal algorithms with denoiser priors to solve inverse problems. These methods rely on the computability of the proximal operator of the data fidelity term. In this paper, we propose a Plug & Play framework based on linearized ADMM that allows us to bypass the computat…

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2020

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

Matias Tassano, Julie Delon, Thomas Veit

CVPR 2020oral

In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture. Until recently, video denoising with neural networks had been a largely under explored domain, and existing methods could not compete with the performance of the best patch-ba…

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