arXiv:2606. 10953v1 Announce Type: new Abstract: Furnished floor plans are fundamental to real estate visualization, interior design, and architectural workflows.
By Fedor Rodionov, Aleksandar Cvejic, Michael Birsak, John Femiani, Peter Wonka
RenoLayout is a new framework that unifies floorplan renovation and furniture layout for residential design. It takes an existing residential layout and a set of design points, then generates a Geometry-as-Code program that preserves immutable structural elements while optimizing furniture placement under design objectives and physical constraints. The authors also introduce a Design Map with 123 fine‑grained design points, a Difference‑Grounded Design‑Point Annotation method, and a three‑stage training pipeline (CPT–SFT–RL) to improve spatial reasoning, instruction following, and constraint compliance. Additionally, they present the RenoLayout Benchmark, a collection of 200 real‑world before‑after renovation cases with complete furniture layouts, marking the first benchmark for unified residential design.
By Jingguo Liu, Yuanqing Liu, Chong Zhang, Yue Yang
arXiv:2512. 16275v2 Announce Type: replace-cross Abstract: Automated floor plan generation lies at the intersection of combinatorial search, geometric constraint satisfaction, and functional design requirements -- a confluence that has historically resisted a unified computational treatment.
By Mohamed Abouagour, Eleftherios Garyfallidis
The paper investigates how conditioned floor plan generation models perform when applied to datasets from different regions, revealing significant performance drops due to domain shift. To address this, the authors create a large synthetic training set that enforces physical constraints while deliberately reducing architectural realism, and show that pre‑training on this data boosts zero‑shot cross‑domain performance and speeds up fine‑tuning in low‑data scenarios.
By Matthieu Ospici, Arnaud Gueze, Luc Bourrat, Adrien Bernhardt
arXiv:2608.29519v1 Announce Type: new
Abstract: We introduce Function-Room Generation, a new indoor 3D scene generation setting that creates rooms supporting explicit functional goals rather than mer...
By Hao Feng, Zhi Zuo, MingJian Liang, Jingyu Hu, Xiaowei Hu, Liupengfei Wu, Dian Zhang, Guoxin Fang, Zhengzhe Liu
arXiv:2608. 07547v1 Announce Type: cross Abstract: Indoor scene layout generation is a challenging task in interior design.
By Yuhao Lu, Weichen Zhang, Wenyi Xiao, Haohui Chen, Yiyun Fei