26 citations · 99 across the 19 of their papers we have counts for
55 papers
Private Set Generation with Discriminative Information
Dingfan Chen, Raouf Kerkouche, Mario Fritz
Differentially private data generation techniques have become a promising solution to the data privacy challenge -- it enables sharing of data while complying with rigorous privacy…
UnGANable: Defending Against GAN-based Face Manipulation
Zheng Li, Ning Yu, Ahmed Salem +3
Deepfakes pose severe threats of visual misinformation to our society. One representative deepfake application is face manipulation that modifies a victim's facial attributes in an…
B-cos Networks: Alignment is All We Need for Interpretability
Moritz Böhle, Mario Fritz, Bernt Schiele
We present a new direction for increasing the interpretability of deep neural networks (DNNs) by promoting weight-input alignment during training. For this, we propose to replace t…
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
Shadi Rahimian, Raouf Kerkouche, Ina Kurth +1
Survival analysis or time-to-event analysis aims to model and predict the time it takes for an event of interest to happen in a population or an individual. In the medical context…
Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers
Apratim Bhattacharyya, Daniel Olmeda Reino, Mario Fritz +1
Accurate prediction of pedestrian and bicyclist paths is integral to the development of reliable autonomous vehicles in dense urban environments. The interactions between vehicle a…
Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
Yang He, Ning Yu, Margret Keuper +1
The rapid advances in deep generative models over the past years have led to highly {realistic media, known as deepfakes,} that are commonly indistinguishable from real to human ey…