English

Pro-DG: Procedural Diffusion Guidance for Architectural Facade Generation

Graphics 2026-05-15 v2 Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning

Abstract

We use hierarchical procedural rules for the generation of control maps within the stable diffusion framework to produce photo-realistic architectural facade images. Starting from a single input image and its segmentation, we apply an inverse procedural module to identify the facade's hierarchical layout. Leveraging this hierarchy and structural features, we introduce a novel ControlNet pipeline that generates new facade imagery guided by procedural transformations. Our method enables various structural edits, including floor duplication and window rearrangement, by integrating hierarchical alignment directly into control maps. This precisely guides the diffusion-based generative process, ensuring local appearance fidelity alongside extensive structural modifications. Comprehensive evaluations, including comparisons with inpainting-based approaches and synthetic benchmarks, confirm our approach's superior capability in preserving architectural identity and achieving accurate, controllable edits. Quantitative results and user feedback validate our method's effectiveness.

Keywords

Cite

@article{arxiv.2504.01571,
  title  = {Pro-DG: Procedural Diffusion Guidance for Architectural Facade Generation},
  author = {Aleksander Plocharski and Jan Swidzinski and Przemyslaw Musialski},
  journal= {arXiv preprint arXiv:2504.01571},
  year   = {2026}
}

Comments

17 pages, 15 figures, Computer Graphics Forum 2026 Journal Paper

R2 v1 2026-06-28T22:43:38.844Z