  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.
