If you're only using a single, unconditioned GAN, the output image is typically only going to be in the 128x128 to 256x256 pixel range, Tyka explained. So to increase the size of these machine-generated images, he stacked multiple, separately trained GANs on top of one another. "The second stage is a superres GAN which [sic] is conditioned on the output of the former," Tyka said. "I.e. in addition to the discriminator loss (which tries to make it look 'real') there is an additional term that makes sure the output is a plausible high-res version of the respective low-res input." This second stage effectively increases the image resolution to 768x768 or 1024x1024 pixels.
By training the second-level (or even third-level) GAN on higher-resolution images of specific facial details like eye, hair and skin texture, it can act as an upscaler for the GANs stacked below it. Eventually Tyka wants to generate 4K-quality pictures, though he's currently having difficulty finding a sufficiently robust data set for training such a system.
Getting the results you see here are easier said than done, however. There was plenty of work to complete before the first simulation ever ran. "GANs are hard to train and hard to control," Tyka explained. "Grooming the input data is important, making sure all images are high-res, don't have artifacts and are not drawings but real photos is time consuming."
What's more, keeping the adversarial networks in sync requires a fair amount of trial and error. "GANs are annoying because there isn't a global objective function. The two networks are each other's objective functions so to speak, so the goalposts are moving," Tyka explained. "It's hard to compare different runs with different parameters because there isn't a good, stable metric for how well a particular net is doing."
Still, Tyka's desired end result for this project does not revolve around accuracy or fidelity. "The goal, like with many art projects, is to make compelling artwork which [sic] inspires or moves or makes you think," he concluded. "That's hard to quantify so I just follow my gut."