In this paper, we propose an adversarial model for producing furniture layout for interior scene synthesis when the interior room is rotated. The proposed model combines a conditional adversarial network, a rotation module, a mode module, and a rotation discriminator module. As compared with the prior work on scene synthesis, our proposed three modules enhance the ability of auto-layout generation and reduce the mode collapse during the rotation of the interior room. We conduct our experiments on a proposed real-world interior layout dataset that contains 14400 designs from the professional designers. Our numerical results demonstrate that the proposed model yields higher-quality layouts for four types of rooms, including the bedroom, the bathroom, the study room, and the tatami room.
Cite
@article{arxiv.2006.13527,
title = {Adversarial Model for Rotated Indoor Scenes Planning},
author = {Xinhan Di and Pengqian Yu and Hong Zhu and Lei Cai and Qiuyan Sheng and Changyu Sun},
journal= {arXiv preprint arXiv:2006.13527},
year = {2020}
}