Synthetic Rainy LiDAR Dataset

该数据集是通过CARLA模拟器在不同雨天气候条件下生成的合成LiDAR点云数据，旨在提高自动驾驶中的感知性能。该数据集包含了4个特征的点云数据，旨在与Waymo开源数据集弥合领域差距，以便更好地训练和评估检测模型。该数据集规模为10,000帧，以10赫兹的频率收集，任务是对恶劣天气条件下的物体进行检测。

This dataset is a synthetic LiDAR point cloud dataset generated using the CARLA simulator under various rainy weather conditions, aiming to improve perception performance in autonomous driving. It contains point cloud data with four features, and is designed to bridge the domain gap compared with the Waymo Open Dataset, so as to better train and evaluate detection models. The dataset consists of 10,000 frames collected at a frequency of 10 Hz, with the task of object detection under adverse weather conditions.