1 code implementation • CVPR 2020 • Qi Chen, Qi Wu, Rui Tang, Yu-Han Wang, Shuai Wang, Mingkui Tan
To this end, we propose a House Plan Generative Model (HPGM) that first translates the language input to a structural graph representation and then predicts the layout of rooms with a Graph Conditioned Layout Prediction Network (GC LPN) and generates the interior texture with a Language Conditioned Texture GAN (LCT-GAN).
no code implementations • 20 Jan 2020 • Zhen-Liang Ni, Gui-Bin Bian, Guan-An Wang, Xiao-Hu Zhou, Zeng-Guang Hou, Xiao-Liang Xie, Zhen Li, Yu-Han Wang
For the scale variation, our adaptive receptive field module aggregates multi-scale features and automatically fuses them with different weights.