Code for "Exploiting Semantic Scene Reconstruction for Estimating Building Envelope Characteristics" (Building and Environment 2025) https://epfl-imos.github.io/buildnet3d.github.io/
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2025-07-09 18:25:10 +02:00
bproc_generator Implementation of BlenderProc Data Generator 2025-07-09 18:25:10 +02:00
buildnet3d/utils Implementation of BlenderProc Data Generator 2025-07-09 18:25:10 +02:00
README.md Implementation of BlenderProc Data Generator 2025-07-09 18:25:10 +02:00

BuildNet3D

Official code for "Exploiting Semantic Scene Reconstruction for Estimating Building Envelope Characteristics" (Building and Environment 2025)

Multi-Modal Imageset Generation

This repository uses BlenderProc to generate multi-modal image data from 3D building models. The rendered outputs include RGB, depth maps, surface normals, semantic labels, and instance segmentations. We implement a simple rule-based sampling method to randomly place camera viewpoints while ensuring the entire object remains within the view. More details are provided here.

The generated buildnet3d image dataset is available here.

Citation

If you find this repository or the associated dataset useful, please cite:

@article{XU2025112731,
      title = {Exploiting semantic scene reconstruction for estimating building envelope characteristics},
      journal = {Building and Environment},
      volume = {275},
      pages = {112731},
      year = {2025},
      issn = {0360-1323},
      doi = {https://doi.org/10.1016/j.buildenv.2025.112731},
      url = {https://www.sciencedirect.com/science/article/pii/S0360132325002136},
      author = {Chenghao Xu and Malcolm Mielle and Antoine Laborde and Ali Waseem and Florent Forest and Olga Fink},
}