A Household Design Method Based on Improved Generative Adversarial Networks

Abstract

We propose a system for automatic household design, which is based on Generative Adversarial Networks (GAN) to construct a multi-layer network structure system. Based on the given home building structure information and in accordance with the real rules, specific furniture objects can be reasonably placed in the corresponding home building space. First, we constructed the household design dataset, which includes a building structure diagram with constraint information as input, and a real home layout based on the structure diagram design. including part of the design and the complete design. The multi-layer GAN structure can generate the household design results with structural relations according to the design steps. The system introduces the attention network, which can generate the structural details in the image by focusing on the constraint conditions of the input image. Conditional regression is designed at the back of the system, so that the generated results can have diverse characteristics. Our system can quickly generate a diversified real home layout, which has good practical value.