13 papers
CommandLM: Data driven behavior level descriptor for ego vehicles
Boris Tokic, Constantin Selzer, Fabian B. Flohr
As autonomous driving systems move toward real-world deployment, interpretable, behavior-level decision-making is essential for safety, trust, and regulation. We introduce CommandL…
Auto-Labelling-Based Domain Transfer for 3D Object Detection on a Bicycle-Mounted LiDAR Platform
Mario Finkbeiner, Max A. Buettner, Kanak Mazumder +1
Reliable 3D perception of vulnerable road users (VRUs) such as cyclists and pedestrians is essential for their safety in urban traffic and a core requirement for autonomous driving…
LIE: LiDAR-only HD Map Construction with Intensity Enhancement via Online Knowledge Distillation
Kanak Mazumder, Fabian B. Flohr
Online High-Definition (HD) map construction is a key component of autonomous driving. Recent methods rely on multi-view camera images for cost-effective HD map segmentation, but c…
WorldVLM: Combining World Model Forecasting and Vision-Language Reasoning
Stefan Englmeier, Katharina Winter, Fabian B. Flohr
Autonomous driving systems depend on on models that can reason about high-level scene contexts and accurately predict the dynamics of their surrounding environment. Vision- Languag…
MASAR: Motion-Appearance Synergy Refinement for Joint Detection and Trajectory Forecasting
Mohammed Amine Bencheikh Lehocine, Julian Schmidt, Frank Moosmann +2
Classical autonomous driving systems connect perception and prediction modules via hand-crafted bounding-box interfaces, limiting information flow and propagating errors to downstr…
DeepUrban: Interaction-Aware Trajectory Prediction and Planning for Automated Driving by Aerial Imagery
Constantin Selzer, Fabian B. Flohr
The efficacy of autonomous driving systems hinges critically on robust prediction and planning capabilities. However, current benchmarks are impeded by a notable scarcity of scenar…