Multi-stage Diffusion Models for Accessible Multi-Occupancy Layout Generation and Human-in-the-loop Refinement

This paper presents a multi-stage diffusion approach for generating accessible and regulation-compliant layouts for multi-occupancy buildings. Existing generative design methods are often limited by rigid one-shot generation, weak constraint adherence, and lack of control over critical architectural features such as openings. To address these limitations, the proposed approach introduces a two-stage latent diffusion model guided by multi-modal input conditions, including boundary constraints, structural wall plans, room masks, spatial anchors, and room type lists, which enable fine-grained yet flexible design control. In addition to generating spatial layouts, a second diffusion model produces doors and windows, guided by rule-assisted annotations that ensure room connectivity and egress compliance. An iterative refinement workflow, supported by a custom web-based user interface featuring both rule-based accessibility checking and human-in-the-loop editing, enables regeneration of specific layout regions to satisfy accessibility requirements and user needs. Furthermore, the finalized 2D layouts are automatically converted into industry foundation class models, which enables direct integration with building information modeling workflows. Quantitative results demonstrate substantial improvements in layout quality, room type accuracy, and opening placement accuracy over existing baselines. Case studies highlight the approach’s capacity for iterative refinement, opening generation, and downstream interoperability. This work establishes a foundation for scalable, constraint-aware generative design in real-world multi-occupancy building scenarios.