Julian Tachella

2 accepted papers

2024

Equivariant Plug-and-Play Image Reconstruction

Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julian Tachella

CVPR 2024poster

Plug-and-play algorithms constitute a popular framework for solving inverse imaging problems that rely on the implicit definition of an image prior via a denoiser. These algorithms can leverage powerful pre-trained denoisers to solve a wide range of imaging tasks circumventing the necessity to train…

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2021

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters

Julian Tachella, Junqi Tang, Mike Davies

CVPR 2021poster

Convolutional Neural Networks (CNNs) are now a well-established tool for solving computational imaging problems. Modern CNN-based algorithms obtain state-of-the-art performance in diverse image restoration problems. Furthermore, it has been recently shown that, despite being highly overparameterized…

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