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As the roadside perception plays an increasingly significant role in theConnected Automated Vehicle Highway(CAVH) technologies, there are immediateneeds of challenging real-world roadside datasets for bench marking andtraining various computer vision tasks such as 2D/3D object detection andmulti-sensor fusion. In this paper, we firstly introduce a challengingBAAI-VANJEE roadside dataset which consist of LiDAR data and RGB imagescollected by VANJEE smart base station placed on the roadside about 4.5m high.This dataset contains 2500 frames of LiDAR data, 5000 frames of RGB images,including 20% collected at the same time. It also contains 12 classes ofobjects, 74K 3D object annotations and 105K 2D object annotations. By providinga real complex urban intersections and highway scenes, we expect theBAAI-VANJEE roadside dataset will actively assist the academic and industrialcircles to accelerate the innovation research and achievement transformation inthe field of intelligent transportation in big data era.

BAAI-VANJEE Roadside Dataset: Towards the Connected Automated Vehicle Highway technologies in Challenging Environments of China