  In this paper, we propose an assistive model that supports professional
interior designers to produce industrial interior decoration solutions and to
meet the personalized preferences of the property owners. The proposed model is
able to automatically produce the layout of objects of a particular indoor
scene according to property owners' preferences. In particular, the model
consists of the extraction of abstract graph, conditional graph generation, and
conditional scene instantiation. We provide an interior layout dataset that
contains real-world 11000 designs from professional designers. Our numerical
results on the dataset demonstrate the effectiveness of the proposed model
compared with the state-of-art methods.

Computer Vision and Pattern Recognition;Machine Learning