  In this paper, we propose a multiple-domain model for producing a custom-size
furniture layout in the interior scene. This model is aimed to support
professional interior designers to produce interior decoration solutions with
custom-size furniture more quickly. The proposed model combines a deep layout
module, a domain attention module, a dimensional domain transfer module, and a
custom-size module in the end-end training. Compared with the prior work on
scene synthesis, our proposed model enhances the ability of auto-layout of
custom-size furniture in the interior room. We conduct our experiments on a
real-world interior layout dataset that contains $710,700$ designs from
professional designers. Our numerical results demonstrate that the proposed
model yields higher-quality layouts of custom-size furniture in comparison with
the state-of-art model.
