6 citations · 14 across the 3 of their papers we have counts for
3 papers
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…
MUVO: A Multimodal Generative World Model for Autonomous Driving with Geometric Representations
Daniel Bogdoll, Yitian Yang, Tim Joseph +2
World models for autonomous driving have the potential to dramatically improve the reasoning capabilities of today's systems. However, most works focus on camera data, with only a…
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving
Daniel Bogdoll, Lukas Bosch, Tim Joseph +3
In recent years there have been remarkable advancements in autonomous driving. While autonomous vehicles demonstrate high performance in closed-set conditions, they encounter diffi…