176 citations · 187 across the 4 of their papers we have counts for
10 papers
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
Ricard Durall, Jireh Jam, Dominik Strassel +2
Facial image manipulation is a generation task where the output face is shifted towards an intended target direction in terms of facial attribute and styles. Recent works have achi…
Combining Transformer Generators with Convolutional Discriminators
Ricard Durall, Stanislav Frolov, Jörn Hees +4
Transformer models have recently attracted much interest from computer vision researchers and have since been successfully employed for several problems traditionally addressed wit…
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…
Latent Space Conditioning on Generative Adversarial Networks
Ricard Durall, Kalun Ho, Franz-Josef Pfreundt +1
Generative adversarial networks are the state of the art approach towards learned synthetic image generation. Although early successes were mostly unsupervised, bit by bit, this tr…
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
Ricard Durall, Margret Keuper, Janis Keuper
Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or vid…
Local Facial Attribute Transfer through Inpainting
Ricard Durall, Franz-Josef Pfreundt, Janis Keuper
The term attribute transfer refers to the tasks of altering images in such a way, that the semantic interpretation of a given input image is shifted towards an intended direction,…