3 papers
cs.CV2026
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…
cs.CV2026
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…
cs.CV2025
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…