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.
翻译：下一代高分辨率汽车雷达(4D雷达)可提供额外的高度测量和密度更高的点云,这极有可能在自主驾驶中进行三维感测。本文介绍一个名为TJ4DRADSet的数据集,其中设有4D雷达点,用于自主驾驶研究。该数据集是在各种驾驶情景中收集的,总共以44个连续序列收集了7757个同步框架,其中附有3D捆绑箱和轨迹识别码。我们为数据集提供了一个基于4D的3D雷达物体探测基线,以展示4D雷达点云的深层学习方法的有效性。该数据集可通过以下链接访问:https://github.com/TJRadarLab/TJ4DRADSet。
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