2 papers
cs.RO2026
MR-LiDAR: A Multi-Resolution Roadside LiDAR Benchmark for Perception Diagnostics and Deployment Guidance
Shunlai Cui, Peng Cao, Yuan Zhu +5
LiDAR model selection is a critical issue in roadside sensing systems, as it directly determines both perception capability and deployment cost. However, the lack of empirical benc…
cs.CV2025
IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain
Zhe Wang, Xiaoliang Huo, Siqi Fan +3
In autonomous driving, The perception capabilities of the ego-vehicle can be improved with roadside sensors, which can provide a holistic view of the environment. However, existing…