FLNet: Graph Constrained Floor Layout Generation
Source
Icmew 2022 IEEE International Conference on Multimedia and Expo Workshops 2022 Proceedings
Date Issued
2022-01-01
Author(s)
Upadhyay, Abhinav
Dubey, Alpana
Arora, Veenu
Kuriakose, Suma Mani
Agarawal, Shaurya
Abstract
In 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.
Subjects
AI Design | Floor Plan | GCN
