Wu, WenmingHu, SizheLiu, LigangZheng, LipingFu, Xiao-MingMasia, BelenThies, Justus2026-04-172026-04-1720261467-8659https://diglib.eg.org/handle/10.1111/cgf70370https://doi.org/10.1111/cgf70370Creating floorplans lays the foundation for architectural design and scene modeling. We propose a novel framework for generating diverse high-quality floorplans under predefined constraints. Central to our method is an iterative refinement process for optimizing the bounding boxes of rooms and the floorplan semantics image, which defines a vector floorplan together. Vector floorplans can be generated through a learning-based refinement process. Our framework supports various constraints, such as floorplan boundaries, topological graphs, and bubble diagrams. Extensive experiments demonstrate that our method is superior to state-of-the-art techniques, particularly in generating a wider variety of solutions that cater to various architectural needs.CC-BY-4.0Computer-aided designShape modeling10.1111/cgf.7037014 pages