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Excellent post. I am dealing with a few of these issues as well..
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The original ProGAN repo provided a config for generating interpolation videos, but that was removed in StyleGAN.
A later independent implementation of backpropagation-only was done by Abdal et
al 2019.) Some of the encodings work well on solo faces & others don’t (on multiple
faces), so sticking close to anime face StyleGAN samples is advised.
Perhaps the way GANs work is that the G is constantly trying to generate samples which are near real datapoints, but then the D ‘repels’ samples too near a real datapoint, so
G orbits around the real datapoints; the D successfully memorizing distinguishing features of each real datapoint breaks the dynamics
because it can either always detect G’s samples or G can get arbitrarily close & it memorize.
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