Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Layout of Custom-size Furniture through Multiple-domain Learning   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.

3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat