Semantic Scholar Open Access 2023

Adapting HouseDiffusion for conditional Floor Plan generation on Modified Swiss Dwellings dataset

Emanuel Kuhn

Abstrak

Automated floor plan generation has recently gained momentum with several methods that have been proposed. The CVAAD Floor Plan Auto-Completion workshop challenge introduced MSD, a new dataset that includes existing structural walls of the building as an additional input constraint. This technical report presents an approach for extending a recent work, HouseDiffusion (arXiv:2211.13287 [cs.CV]), to the MSD dataset. The adaption involves modifying the model's transformer layers to condition on a set of wall lines. The report introduces a pre-processing pipeline to extract wall lines from the binary mask of the building structure provided as input. Additionally, it was found that a data processing procedure that simplifies all room polygons to rectangles leads to better performance. This indicates that future work should explore better representations of variable-length polygons in diffusion models. The code will be made available at a later date.

Topik & Kata Kunci

Penulis (1)

E

Emanuel Kuhn

Format Sitasi

Kuhn, E. (2023). Adapting HouseDiffusion for conditional Floor Plan generation on Modified Swiss Dwellings dataset. https://doi.org/10.48550/arXiv.2312.03938

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →
Lihat di Sumber doi.org/10.48550/arXiv.2312.03938
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Sumber Database
Semantic Scholar
DOI
10.48550/arXiv.2312.03938
Akses
Open Access ✓