Generating Building Infrastructure Modeling Using cGAN

Abstract

In today’s world to propose a building model to an investor and builder, an architect has to undergo a full process of making a full 3D model of a building and detailing each and every aspect of the building. The details include the interior and exterior of the building. But, at the end the investor and builder are interested in the front elevation design of the building and not the detailed part. Hence, for providing the important information like faces of the building, we propose to generate new synthetic versions of images from sketch, labels, and edges. The model used for developing this platform i.e., pix2pix is an approach for training CNN for image-to-image translations. Pix2pix can be demonstrated on various image translation tasks; transforming an image from one domain to another or to a corresponding output could have innumerable applications, changing art styles, building infrastructure modelling and criminal identification are just a few applications. The building infrastructure modeling platform proposed aims to be feasible and have wide applicability for the architects by providing an interactive pallet and a convenient platform.