176 citations · 185 across the 7 of their papers we have counts for
17 papers
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space
Kalun Ho, Franz-Josef Pfreundt, Janis Keuper +1
Over the last decade, the development of deep image classification networks has mostly been driven by the search for the best performance in terms of classification accuracy on sta…
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain
Paula Harder, Franz-Josef Pfreundt, Margret Keuper +1
Despite the success of convolutional neural networks (CNNs) in many computer vision and image analysis tasks, they remain vulnerable against so-called adversarial attacks: Small, c…
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…
Module Intersection for the Integration-by-Parts Reduction of Multi-Loop Feynman Integrals
Dominik Bendle, Janko Boehm, Wolfram Decker +4
In this manuscript, which is to appear in the proceedings of the conference "MathemAmplitude 2019" in Padova, Italy, we provide an overview of the module intersection method for th…
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.…
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,…