Although deep learning techniques have brought unprecedented accuracy to automatic
building extraction, several main issues still constitute an obstacle to effective and practical …

Mixed reality (MR) devices capture 3D spatial maps of users' surroundings to integrate
virtual content into their physical environment. Existing permission models implemented in …

In this paper, we propose a dynamic 3D object detector named HyperDet3D, which is
adaptively adjusted based on the hyper scene-level knowledge on the fly. Existing methods …

3D visual recognition is a prerequisite for most autonomous robotic systems operating in the
real world. It empowers robots to perform a variety of tasks, such as tracking, understanding …

Autonomous navigation in unstructured vegetated environments remains an open
challenge. To successfully operate in these settings, autonomous ground vehicles (AGVs) …

An obstacle element map is the basis of indoor navigation space subdivision. Effective and
reasonable indoor space subdivision can improve the fineness of indoor navigation path …

Ground filtering (GF) is a fundamental step for airborne laser scanning (ALS) data
processing. The advent of deep learning techniques provides new solutions to this problem …

Autonomous navigation in unstructured vegetated environments remains an open
challenge. To successfully operate in these settings, ground vehicles must assess the …

The scale and quality of point cloud datasets constrain the advancement of point cloud
learning. Recently, with the development of multi-modal learning, the incorporation of …

In autonomous vehicles, understanding the surrounding 3D environment of the ego vehicle
in real-time is essential. A compact way to represent scenes while encoding geometric …