HouseNet contains select 'house' and 'villa' models that originated from the BuildingNet v0.1 data set (Pratheba, et al.) which were then preprocessed to remove site geometry and relabeled to only include the 'door', 'roof', 'wall', and 'window' labels since these labels were in all models. For each building in this data set, the following files are included:
1) a modified point cloud file (.ply) which came from the original data set and was modified by removing site geometry and relabeling the points to make the models suited for deep learning for generative design
2) a modified file containing label information (.json) which came from the original data set and was modified to make the models suited for deep learning for generative design
3) a pickle file (.pkl) generated through pre-processing which contains information about the point cloud including the file name, label array, color array, typology, and building type information
Pratheba Selvaraju, Mohamed Nabail, Marios Loizou, Maria Maslioukova, Melinos Averkiou, Andreas Andreou, Siddhartha Chaudhuri, Evangelos Kalogerakis, "BuildingNet: Learning to Label 3D Buildings", Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021. https://buildingnet.org/
" authors: - family-names: Mueller given-names: Lisa-Marie title: "HouseNet (select preprocessed models from BuildingNet 0.1)" keywords: version: 1 identifiers: - type: doi value: 10.4121/4d82052e-650c-4775-8bd9-623df68991b6.v1 license: CC0 date-released: 2023-06-20