176 citations · 262 across the 15 of their papers we have counts for
9 papers · 1 filter
Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets
Patrick Grommelt, Louis Weiss, Franz-Josef Pfreundt +1
The widespread adoption of generative image models has highlighted the urgent need to detect artificial content, which is a crucial step in combating widespread manipulation and mi…
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…
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,…
Semi Few-Shot Attribute Translation
Ricard Durall, Franz-Josef Pfreundt, Janis Keuper
Recent studies have shown remarkable success in image-to-image translation for attribute transfer applications. However, most of existing approaches are based on deep learning and…
Object Segmentation using Pixel-wise Adversarial Loss
Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe +1
Recent deep learning based approaches have shown remarkable success on object segmentation tasks. However, there is still room for further improvement. Inspired by generative adver…
TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization
Dominik Marek Loroch, Norbert Wehn, Franz-Josef Pfreundt +1
Recent research implies that training and inference of deep neural networks (DNN) can be computed with low precision numerical representations of the training/test data, weights an…