161 citations · 338 across the 33 of their papers we have counts for
8 papers · 1 filter
Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation
Svetlana Pavlitska, Enrico Eisen, J. Marius Zöllner
Vulnerability to adversarial attacks is a well-known deficiency of deep neural networks. Larger networks are generally more robust, and ensembling is one method to increase adversa…
Evaluating Adversarial Attacks on Traffic Sign Classifiers beyond Standard Baselines
Svetlana Pavlitska, Leopold Müller, J. Marius Zöllner
Adversarial attacks on traffic sign classification models were among the first successfully tried in the real world. Since then, the research in this area has been mainly restricte…
TLD-READY: Traffic Light Detection -- Relevance Estimation and Deployment Analysis
Nikolai Polley, Svetlana Pavlitska, Yacin Boualili +4
Effective traffic light detection is a critical component of the perception stack in autonomous vehicles. This work introduces a novel deep-learning detection system while addressi…
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving
Daniel Bogdoll, Jan Imhof, Tim Joseph +2
In autonomous driving, the most challenging scenarios can only be detected within their temporal context. Most video anomaly detection approaches focus either on surveillance or tr…
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving
Daniel Bogdoll, Noël Ollick, Tim Joseph +2
Dealing with atypical traffic scenarios remains a challenging task in autonomous driving. However, most anomaly detection approaches cannot be trained on raw sensor data but requir…
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving
Daniel Bogdoll, Iramm Hamdard, Lukas Namgyu Rößler +9
The scale-up of autonomous vehicles depends heavily on their ability to deal with anomalies, such as rare objects on the road. In order to handle such situations, it is necessary t…
CAGE: Circumplex Affect Guided Expression Inference
Niklas Wagner, Felix Mätzler, Samed R. Vossberg +3
Understanding emotions and expressions is a task of interest across multiple disciplines, especially for improving user experiences. Contrary to the common perception, it has been…
Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions
Daniel Bogdoll, Jing Qin, Moritz Nekolla +3
Reinforcement Learning is a highly active research field with promising advancements. In the field of autonomous driving, however, often very simple scenarios are being examined. C…