This is the implementation of the following paper: PCC-HAUS: Point Cloud Completion framework for High-Altitude Urban Scanning. This repository contains the PCC-HAUS framework for restoring large, incomplete point clouds of buildings with the use of point cloud completion models designed for small data. The framework is dedicated to high-altitude lidar scans.
The Third-Party directory provides several state-of-the-art point cloud completion frameworks with new features, along with instructions for setting up a shared Python environment with CUDA support.
The Framework directory provides the source code of PCC-HAUS along with detailed usage instructions.
Please refer to the Wiki for detailed installation and usage instructions.
If you find this work useful in your research, please consider citing:
@article{KULAWIAK2026102982,
title = {PCC-HAUS: Point cloud completion framework for high-altitude urban scanning},
author = {Marek Kulawiak},
journal = {SoftwareX},
volume = {35},
pages = {102982},
year = {2026},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2026.102982},
url = {https://www.sciencedirect.com/science/article/pii/S2352711026004735}
}