no not naive at all. this method isn't specific for just extracting features from faces. it can disentangles features from any kind of images. in fact, the next dataset i might train on is on flowers (or birds)
OK, my point is what could be done beyond generating images in some style? Can we generate interesting mock data given a database for instance (of course this is exactly what you did in a way, but I have in mind e.g. a database containing some numerical/categorical features known to a specific accuracy)?
You can use GANs to generate fake data based on stuff like particle accelerator data or electronic health records. Whether you can use StyleGAN specifically is unclear. What's the equivalent of progressive growing on tabular/numeric data? Or style transfer?