  Ever since the prevalent use of the LiDARs in autonomous driving, tremendous
improvements have been made to the learning on the point clouds. However,
recent progress largely focuses on detecting objects in a single 360-degree
sweep, without extensively exploring the temporal information. In this report,
we describe a simple way to pass such information in the learning pipeline by
adding timestamps to the point clouds, which shows consistent improvements
across all three classes.
