Interest in semantic segmentation of 3D point clouds using ML and DL has grown due to
their key role in scene insight across a wide range of computer vision, robotics and remote …

The rapidly expanding field of Scan-to-BIM applications highlights the importance of model
uncertainty assessment in describing the quality of modeling results. Although there have …

Deep learning (DL) on point clouds holds significant potential in the construction industry,
yet no comprehensive review has thoroughly summarized its applications and shortcomings …

The development of BIM (Building Information Modeling) parametric modeling technology
has improved the reusability and modeling efficiency of building information models. Aiming …

In spite of recent advances, a significant disparity between automatically reconstructed
building information models (BIMs) and real scenes persists, particularly within complex …

Falls from scaffolds cause the majority of accidents and fatalities at construction sites. A
deep learning-based 3D reconstruction technology could provide a solution to prevent such …

The measurement of reference pose and geometric size for space non-cooperative targets is
an essential premise of on-orbit servicing. In this paper, a three-dimensional (3-D) …

Large volumes of 3D parametric datasets, such as building information modeling (BIM), are
the foundation for developing and applying smart city and digital twin technologies. Those …

Existing buildings' geometry digitisation using Point Cloud Datasets is important. This is
evident given the lack of digital as-designed models for older buildings, which can serve as …

Automatically converting three-dimensional (3D) point clouds into building information
modeling (BIM) has been an active research area over the past few years. However, existing …