论文标题
利用时间信息进行3D检测和域的适应
Leveraging Temporal Information for 3D Detection and Domain Adaptation
论文作者
论文摘要
自从普遍使用激光雷达在自动驾驶中，对点云的学习进行了巨大改进。但是，最近的进展主要集中在单个360度扫描中检测对象，而无需广泛探索时间信息。在本报告中，我们描述了一种简单的方法来通过将时间戳添加到点云中，以传递学习管道中的此类信息，该时间戳在所有三个类中都显示出一致的改进。
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.
