  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.
