3D building fabrication with geometry and texture coordination via hybrid GAN

Abstract

3D building plays the essential role in digital city construction, city augmented reality and smart urban planning & design. Conventional building construction is accomplished by modeling software which requires significant human intervention. In this paper, a method of 3D building fabrication via Hybrid generative adversarial network (GAN) is proposed, in which a loss function with the introduction of cycle consistency loss and perceptual loss is given, a multi-properties GAN chain is built to create the building with complex architectures. Additionally, a mixed GAN network to generate the geometry and texture coordination is put forward. The discussed method can refine rough architectural models for outputting realistic buildings. Experiments show that generated 3D buildings utilizing the presented method are realistic, with geometry and textural consistency, which improves performance by 20% over traditional methods.