176 citations · 336 across the 51 of their papers we have counts for
8 papers · 1 filter
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…
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches
Kalun Ho, Janis Keuper, Franz-Josef Pfreundt +1
In this work, we evaluate two different image clustering objectives, k-means clustering and correlation clustering, in the context of Triplet Loss induced feature space embeddings.…
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…
PHS: A Toolbox for Parallel Hyperparameter Search
Peter Michael Habelitz, Janis Keuper
We introduce an open source python framework named PHS - Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python…
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts
Kalun Ho, Janis Keuper, Margret Keuper
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowled…
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,…
Scalable Hyperparameter Optimization with Lazy Gaussian Processes
Raju Ram, Sabine Müller, Franz-Josef Pfreundt +2
Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic s…