14 citations · 29 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
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…