TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving - Zheng, Lianqing; Ma, Zhixiong; Zhu, Xichan; Tan, Bin; Li, Sen; Long, Kai; Sun, Weiqi; Chen, Sihan; Zhang, Lu; Wan, Mengyue; Huang, Libo; Bai, Jie (2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022)
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.