FCGF extracts geometric features from 3D scans or point clouds using a single-pass fully-convolutional network, achieving state-of-the-art accuracy without preprocessing. The model produces compact 32-dimensional features and is optimized for speed with MinkowskiEngine sparse tensor operations on GPU. It is designed for applications like 3D registration, reconstruction, and tracking in both indoor and outdoor scenes.