8 citations · 8 across the 4 of their papers we have counts for
4 papers
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems
Maud Biquard, Marie Chabert, Florence Genin +2
Poisson-Gaussian noise describes the noise of various imaging systems thus the need of efficient algorithms for Poisson-Gaussian image restoration. Deep learning methods offer stat…
Deep priors for satellite image restoration with accurate uncertainties
Biquard Maud, Marie Chabert, Florence Genin +2
Satellite optical images, upon their on-ground receipt, offer a distorted view of the observed scene. Their restoration, including denoising, deblurring, and sometimes super-resolu…
Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection
Colin Decourt, Rufin VanRullen, Didier Salle +1
In recent years, driven by the need for safer and more autonomous transport systems, the automotive industry has shifted toward integrating a growing number of Advanced Driver Assi…
Variational Bayes image restoration with compressive autoencoders
Maud Biquard, Marie Chabert, Florence Genin +2
Regularization of inverse problems is of paramount importance in computational imaging. The ability of neural networks to learn efficient image representations has been recently ex…