4 papers
AerialFusionMapNet: Online HD Map Construction with Aerial-Onboard BEV Fusion
Daniel Lengerer, Mathias Pechinger, Klaus Bogenberger +1
High-resolution aerial imagery has recently emerged as a complementary modality for automated driving perception and has shown potential to improve birds-eye-view (BEV) scene under…
Learning Ego-Centric BEV Representations from a Perspective-Privileged View: Cross-View Supervision for Online HD Map Construction
Daniel Lengerer, Mathias Pechinger, Klaus Bogenberger +1
Bird's-eye-view (BEV) representations derived from multi-camera input have become a central interface for online high-definition (HD) map construction. However, most approaches rel…
Cross-Stage Coherence in Hierarchical Driving VQA: Explicit Baselines and Learned Gated Context Projectors
Gautam Kumar Jain, Carsten Markgraf, Julian Stähler
Graph Visual Question Answering (GVQA) for autonomous driving organizes reasoning into ordered stages, namely Perception, Prediction, and Planning, where planning decisions should…
AID4AD: Aerial Image Data for Automated Driving Perception
Daniel Lengerer, Mathias Pechinger, Klaus Bogenberger +1
This work investigates the integration of spatially aligned aerial imagery into perception tasks for automated vehicles (AVs). As a central contribution, we present AID4AD, a publi…