aalto1 untyped-item.component.html
Generation of realistic floorplans using diffusion-based models
Loading...
URL
Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
Department
Mcode
SCI3044
Language
en
Pages
32
Series
Abstract
Existing studies on automatic floor plan generation have been mainly focused on the room layout of the floorplans while ignoring fenestration and furniture details, which was justified by the fact that these details are often irrelevant for the user. In this thesis, we propose to generate floorplans using diffusion-based generative models trained on images that contain fenestration and furniture information. Our experiments suggest this approach results in more realistic floorplans in comparison to previous generative models such as HouseGAN++. We also show that the proposed diffusion-based generative models can be used for reconstructing missing information in existing floorplans, for example, missing labels of the room types.