2 citations · 2 across the 1 of their papers we have counts for
4 papers
Patch-Craft Self-Supervised Training for Correlated Image Denoising
Gregory Vaksman, Michael Elad
Supervised neural networks are known to achieve excellent results in various image restoration tasks. However, such training requires datasets composed of pairs of corrupted images…
Patch Craft: Video Denoising by Deep Modeling and Patch Matching
Gregory Vaksman, Michael Elad, Peyman Milanfar
The non-local self-similarity property of natural images has been exploited extensively for solving various image processing problems. When it comes to video sequences, harnessing…
Stochastic Image Denoising by Sampling from the Posterior Distribution
Bahjat Kawar, Gregory Vaksman, Michael Elad
Image denoising is a well-known and well studied problem, commonly targeting a minimization of the mean squared error (MSE) between the outcome and the original image. Unfortunatel…
LIDIA: Lightweight Learned Image Denoising with Instance Adaptation
Gregory Vaksman, Michael Elad, Peyman Milanfar
Image denoising is a well studied problem with an extensive activity that has spread over several decades. Despite the many available denoising algorithms, the quest for simple, po…