In the realm of modern autonomous driving, the perception system is indispensable for
accurately assessing the state of the surrounding environment, thereby enabling informed …

LiDAR and cameras are complementary sensors for 3D object detection in autonomous
driving. However, it is challenging to explore the unnatural interaction between point clouds …

The 3-D object detection with light detection and ranging (LiDAR) point clouds is a
challenging problem, which requires 3-D scene understanding, yet this task is critical to …

Although the majority of recent autonomous driving systems concentrate on developing
perception methods based on ego-vehicle sensors, there is an overlooked alternative …

LiDAR-camera fusion can enhance the performance of 3D object detection by utilizing
complementary information between depth-aware LiDAR points and semantically rich …

Monocular 3D object detection has recently shown promising results, however there remain
challenging problems. One of those is the lack of invariance to different camera intrinsic …

Monocular 3D vehicle localization is an important task for vehicle behaviour analysis, traffic
flow parameter estimation and autonomous driving in Intelligent Transportation System (ITS) …

Abstract 3D objection detection is a key task in autonomous driving. Because 3D structure
information is lost during perspective projection, 3D localization of an object from monocular …

Abstract Unmanned Aerial Vehicles (UAVs) exhibit superior maneuverability and large-scale
movement capability in 3D space, making them ideal platforms for various autonomous …

Representing the world in 3D space provides vivid texture and depth information. However,
3D datasets currently do not match the scale of 2D datasets. There is a growing trend in …