Accurate 3D object detection from point clouds is critical for autonomous vehicles. However,
point cloud data collected by LiDAR sensors are inherently sparse, especially at long …

With the advancement of 3D sensing technologies, point clouds are gradually becoming the
main type of data representation in applications such as autonomous driving, robotics, and …

At present, the learning-based down-sampling method has achieved good result by using
the loss of subsequent tasks to optimize the process of sampling points selection. However …

Point clouds consist of 3D data points and are among the most considerable data formats for
3D representations. Their popularity is due to their broad application areas, such as robotics …

High-speed rails have strategic significance for political and economic development. As a
critical part of the power supply system, overhead catenary systems (OCSs) power high …

3D object detection by autonomous vehicles is integral to intelligent transportation. Existing
systems often compromise essential foreground point features and local spatial interactions …

Human environments are designed and managed by humans for humans. Thus, adding
robots to interact with humans and perform specific tasks appropriately is an essential topic …

Three-dimensional virtual environments can be configured as test environments of
autonomous things, and remote sensing by 3D point clouds collected by light detection and …

Point clouds have evolved into one of the most important data formats for 3D representation.
It is becoming more popular as a result of the increasing affordability of acquisition …

As vital infrastructures, high-speed railways support the development of transportation. To
maintain the punctuality and safety of railway systems, researchers have employed manual …