Upadhyay, AbhinavAbhinavUpadhyayDubey, AlpanaAlpanaDubeyArora, VeenuVeenuAroraKuriakose, Suma ManiSuma ManiKuriakoseAgarawal, ShauryaShauryaAgarawal2025-08-312025-08-312022-01-01[9781665472180]10.1109/ICMEW56448.2022.98593502-s2.0-85138111503http://repository.iitgn.ac.in/handle/IITG2025/26296In this work, we propose a generative-based approach, FLNet, to synthesize floor layout plans guided by user constraints. Our approach considers user inputs in the form of boundary, room types, and spatial relationships and generates the layout design satisfying these requirements. We evaluated our approach on floor plans data, RPLAN, consisting of 80,000 vector-graphics floor plans of residential buildings designed by professional architects. We perform both qualitative and quantitative analysis along three metrics - Layout generation accuracy, Realism, and Quality to evaluate the generated layout designs. We compare our approach with the existing baselines and outperform on all these metrics. The layout designs generated by our approach are more realistic and of better quality.falseAI Design | Floor Plan | GCNConference Paper20228cpConference Proceeding10