176 citations · 255 across the 11 of their papers we have counts for
4 papers · 1 filter
Investigating Shifts in GAN Output-Distributions
Ricard Durall, Janis Keuper
A fundamental and still largely unsolved question in the context of Generative Adversarial Networks is whether they are truly able to capture the real data distribution and, conseq…
Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues
Ricard Durall, Avraam Chatzimichailidis, Peter Labus +1
Generative adversarial networks (GANs) provide state-of-the-art results in image generation. However, despite being so powerful, they still remain very challenging to train. This i…
Unmasking DeepFakes with simple Features
Ricard Durall, Margret Keuper, Franz-Josef Pfreundt +1
Deep generative models have recently achieved impressive results for many real-world applications, successfully generating high-resolution and diverse samples from complex datasets…
Stabilizing GANs with Soft Octave Convolutions
Ricard Durall, Franz-Josef Pfreundt, Janis Keuper
Motivated by recently published methods using frequency decompositions of convolutions (e.g. Octave Convolutions), we propose a novel convolution scheme to stabilize the training a…