论文标题
Cirrus：远程双图案激光雷达数据集
Cirrus: A Long-range Bi-pattern LiDAR Dataset
论文作者
论文摘要
在本文中，我们介绍了Cirrus，这是一种新的远程Bi-Pattern LiDAR公共数据集，用于自动驾驶任务，例如3D对象检测，对高速公路驾驶至关重要，并且及时决策。我们的平台配备了高分辨率摄像机和一对具有250米有效范围的LiDAR传感器，其比现有公共数据集的长大。我们使用高斯和统一扫描模式同时记录配对点云。在如此远距离的情况下，点密度差异很大，不同的扫描模式进一步使LIDAR中的对象表示多样化。在卷心菜中，在整个有效范围内，在激光雷德点云中详尽地注释了八种对象。为了说明该新数据集支持的研究类型，我们介绍了不同范围，扫描模式和传感器设备的LiDAR模型适应。有希望的结果表明，该新数据集对机器人和计算机视觉社区的巨大潜力。
In this paper, we introduce Cirrus, a new long-range bi-pattern LiDAR public dataset for autonomous driving tasks such as 3D object detection, critical to highway driving and timely decision making. Our platform is equipped with a high-resolution video camera and a pair of LiDAR sensors with a 250-meter effective range, which is significantly longer than existing public datasets. We record paired point clouds simultaneously using both Gaussian and uniform scanning patterns. Point density varies significantly across such a long range, and different scanning patterns further diversify object representation in LiDAR. In Cirrus, eight categories of objects are exhaustively annotated in the LiDAR point clouds for the entire effective range. To illustrate the kind of studies supported by this new dataset, we introduce LiDAR model adaptation across different ranges, scanning patterns, and sensor devices. Promising results show the great potential of this new dataset to the robotics and computer vision communities.
