Deep neural network approaches to inverse imaging problems have produced impressive
results in the last few years. In this survey paper, we consider the use of generative models …

This article proposes a novel approach to regularize the ill-posed and non-linear blind
image deconvolution (blind deblurring) using deep generative networks as priors. We …

Deep learning-based face recognition (FR) systems pose significant privacy risks by tracking
users without their consent. While adversarial attacks can protect privacy, they often produce …

Retinal images acquired using fundus cameras often contain visual artifacts due to imperfect
imaging conditions, refractive medium turbidity, and motion blur. In addition, ocular diseases …

Motion blur in videos captured by autonomous vehicles and robots can degrade their
perception capability. In this work, we present a novel approach to video deblurring by fitting …

This research presents a method for image deblurring using generative adversarial
networks (GAN). Blurry images often lack detail and affect image quality. This work tackles …