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Found 4 papers, 1 papers with code
Adversarial Likelihood Estimation With One-Way Flows
Generative Adversarial Networks (GANs) can produce high-quality samples, but do not provide an estimate of the probability density around the samples.
LED: Latent Variable-based Estimation of Density
Modern generative models are roughly divided into two main categories: (1) models that can produce high-quality random samples, but cannot estimate the exact density of new data points and (2) those that provide exact density estimation, at the expense of sample quality and compactness of the latent space.
GIF: Generative Interpretable Faces
Specifically, we condition StyleGAN2 on FLAME, a generative 3D face model.
DRCAS: Deep Restoration Network for Hardware Based Compressive Acquisition Scheme
Bearing these concerns in mind, we propose DRCAS (Deep Restoration network for hardware based Compressed Acquisition Scheme), which to our best knowledge, is the first work proposed in the literature for restoration of images acquired using acquisition scheme like HCAS.
