Generative Multi-Adversarial Networks

ICLR, Volume abs/1611.01673, 2017.

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We introduced multiple discriminators into the Generative adversarial networks framework and explored discriminator roles ranging from a formidable adversary to a forgiving teacher

Abstract:

Generative adversarial networks (GANs) are a framework for producing a generative model by way of a two-player minimax game. In this paper, we propose the \emph{Generative Multi-Adversarial Network} (GMAN), a framework that extends GANs to multiple discriminators. In previous work, the successful training of GANs requires modifying the ...More

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