A Unified Benchmark for Aerial-Enhanced Autonomous Driving: The KITScenes Aerial Dataset
Read the original on Hugging Face Trending Papers →The paper introduces KITScenes Aerial, an extension of the KITScenes Multimodal dataset that adds synchronized aerial imagery and high‑resolution neural representations to existing onboard sensor data, vehicle poses, and Lanelet2 map annotations. It evaluates mapping across all 53 KITScenes map classes, showing that aerial context significantly improves fine‑grained and extended‑range mapping, with higher‑resolution imagery boosting performance further, especially for challenging elements like traffic lights. The study also assesses cross‑view localization under geographically disjoint conditions, achieving a mean translation error of 5.13 m with a fine‑grained feature‑matching baseline.
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