Publication | Closed Access
TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving
106
Citations
14
References
2022
Year
EngineeringMachine LearningPoint Cloud ProcessingPoint Cloud3D Computer VisionImage AnalysisData ScienceImaging RadarRadar Signal ProcessingComputational GeometryRadar PointsMachine VisionSynthetic Aperture RadarRadar ApplicationAutonomous DrivingDeep Learning3D Object RecognitionComputer VisionRadar ImagingRadarObject Detection Baseline3D VisionRadar Dataset
The next-generation high-resolution automotive radar (4D radar) can provide additional elevation measurement and denser point clouds, which has great potential for 3D sensing in autonomous driving. In this paper, we introduce a dataset named TJ4DRadSet with 4D radar points for autonomous driving research. The dataset was collected in various driving scenarios, with a total of 7757 synchronized frames in 44 consecutive sequences, which are well annotated with 3D bounding boxes and track ids. We provide a 4D radar-based 3D object detection baseline for our dataset to demonstrate the effectiveness of deep learning methods for 4D radar point clouds. The dataset can be accessed via the following link: https://github.com/TJRadarLab/TJ4DRadSet.
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