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PnP-ReG: Learned Regularizing Gradient for Plug-and-Play Gradient Descent
We show that it is possible to train a network directly modeling the gradient of a MAP regularizer while jointly training the corresponding MAP denoiser.
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration
Plug-and-Play optimization recently emerged as a powerful technique for solving inverse problems by plugging a denoiser into a classical optimization algorithm.
A Fourier Disparity Layer representation for Light Fields
In this paper, we present a new Light Field representation for efficient Light Field processing and rendering called Fourier Disparity Layers (FDL).
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