论文标题
Boreas：一个多季节的自动驾驶数据集
Boreas: A Multi-Season Autonomous Driving Dataset
论文作者
论文摘要
在一年的时间内通过重复的路线来收集Boreas数据集，从而导致季节性变化和不利的天气状况，例如降雨和降雪。总体而言，BOREAS数据集包括超过350公里的驾驶数据，其中包含128通道的Velodyne Alpha Prime Lidar，360 $^\ CICC $ NAVTECH CIR304-H扫描雷达，5MP Flir Blackfly S摄像头和毫秒毫无用处的后置地面真理真理。我们的数据集将支持实时排行榜进行探光，度量定位和3D对象检测。数据集和开发套件可从https://www.boreas.utias.utoronto.ca获得。
The Boreas dataset was collected by driving a repeated route over the course of one year, resulting in stark seasonal variations and adverse weather conditions such as rain and falling snow. In total, the Boreas dataset includes over 350km of driving data featuring a 128-channel Velodyne Alpha Prime lidar, a 360$^\circ$ Navtech CIR304-H scanning radar, a 5MP FLIR Blackfly S camera, and centimetre-accurate post-processed ground truth poses. Our dataset will support live leaderboards for odometry, metric localization, and 3D object detection. The dataset and development kit are available at https://www.boreas.utias.utoronto.ca
