InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs
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DOI: 10.1109/tpami.2020.3034267
Abstract: Although Generative Adversarial Networks (GANs) have made significant progress in face synthesis, there lacks enough understanding of what GANs have learned in the latent representation to map a randomly sampled code to a photo-realistic face… read more here.
Keywords: face representation; representation learned; disentangled face; face ... See more keywords