Conditional GANs with Auxiliary Discriminative Classifier. (arXiv:2107.10060v5 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2107.10060

Conditional generative models aim to learn the underlying joint distribution
of data and labels to achieve conditional data generation. Among them, the
auxiliary classifier generative adversarial network (AC-GAN) has been widely
used, but suffers from the problem of low intra-class diversity of the
generated samples. The fundamental reason pointed out in this paper is that the
classifier of AC-GAN is generator-agnostic, which therefore cannot provide
informative guidance for the generator to approach the joint distribution,
resulting in a minimization of …

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