ArcoGAN


Ongoing Research on 3D GAN
Fall 2021











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The arch compositional agency has historically fluctuated between order and subversion. Architectural imagery of this compositional range has been extensively documented on multiple mediums throughout history, which makes for a good case study for machine learning. This project undertakes the challenge of tridimensionalizing 2D GAN-produced latent imagery through a series of workflows that engage datasets as an animated computable matter from which to choose specific cross-sections or moments, ultimately defying or questioning the designer’s role in an AI-based design process. The exhibits search to operate within the most trending digitized mediums, embracing the instrumentality of social media and NFT culture in AI and current architectural representation.

Made using machine learning workflows.




Type:               Ongoing Research
Research:      Machine Learning, 2D & 3D GAN.



1. Generative StyleGAN.
2. New-Found 3D GAN arch facade typologies.
3. Morphing 3D GANs.















CARLOS NAVARRO      LOS ANGELES, CA