Progressive Growing of GANs for Improved Quality, Stability, and Variation

international conference on learning representations, 2018.

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Abstract:

We describe a new training methodology for generative adversarial networks. The key idea is to grow both the generator and discriminator progressively: starting from a low resolution, we add new layers that model increasingly fine details as training progresses. This both speeds the training up and greatly stabilizes it, allowing us to pr...More

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