Specifically, InterFaceGAN is capable of turning an unconditionally trained face synthesis model to controllable GAN by interpreting the very first latent space and finding the hidden semantic ...
Finally, we suggest a new metric for evaluating GAN results, both in terms of image quality and variation. As an additional contribution, we construct a higher-quality version of the CelebA dataset.
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