The 3D point cloud (3DPC) has significantly evolved and benefited from the advance of
deep learning (DL). However, the latter faces various issues, including the lack of data or …

Abstract Computer-Aided Design (CAD) model reconstruction from point clouds is an
important problem at the intersection of computer vision graphics and machine learning; it …

Traditional shape descriptors have been gradually replaced by convolutional neural
networks due to their superior performance in feature extraction and classification. The state …

Urban simulations that involve disaster prevention, urban design, and assisted navigation
heavily rely on urban geometric models. While large urban areas need a lot of time to be …

Using augmented reality for subsurface utility engineering (SUE) has benefited from recent
advances in sensing hardware, enabling the first practical and commercial applications …

Automated generation of geometric models from point cloud data holds significant
importance in the field of computer vision and has expansive applications, such as shape …

Modern computer-aided design (CAD) adopts history-based parametric modeling paradigm,
in which the sketches play a crucial role to represent the design history, design intent, and …

In this paper, we present a novel method for point cloud registration in large-scale 3D
scenes. Our approach is accurate and robust, and does not rely on unrealistic assumptions …

Geometric building models are essential in BIM technology. The reconstruction results using
current methods are usually represented using mesh, which is limited to visualization …

We introduce a novel computational paradigm for reconstructing solid computer-aided
design (CAD) features from the surface of a segmented manifold triangular mesh. This …