TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving (2204.13483v3)
Abstract: 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.
- Lianqing Zheng (8 papers)
- Zhixiong Ma (5 papers)
- Xichan Zhu (7 papers)
- Bin Tan (11 papers)
- Sen Li (60 papers)
- Kai Long (4 papers)
- Weiqi Sun (10 papers)
- Sihan Chen (39 papers)
- Lu Zhang (373 papers)
- Mengyue Wan (1 paper)
- Libo Huang (23 papers)
- Jie Bai (12 papers)