Point Cloud City Open3D ML Repository

Point Cloud City (PCC) was developed during the 2018 NIST Public Safety Innovation Accelerator Program - PCC awardees generated an extensive catalog of annotated 3D indoor point clouds that can be used by industry, academia, and government to advance research and development in the areas of indoor mapping, localization and navigation for public safety, as well as to demonstrate the potential value of ubiquitous indoor positioning and location-based information.

This GitHub repository extends Open3D-ML to integrate the Point Cloud City datasets and features the processing code, dataset pipeline, and machine learning model configuration files.

Open3D-ML is an extension of Open3D for 3D machine learning tasks. It builds on top of the Open3D core library and extends it with machine learning tools for 3D data processing. This repo focuses on applications such as semantic point cloud segmentation and provides pretrained models that can be applied to common tasks as well as pipelines for training.

Open3D-ML-PointCloudCity works with TensorFlow and PyTorch to integrate easily into existing projects and also provides general functionality independent of ML frameworks such as data visualization.