Advanced Deep Learning with Keras

Chapter 6
Implementation of StackedGAN in Keras
The detailed network model of StackedGAN can be seen in the following figure.
For conciseness, only two encoder-GANs per stack are shown. The figure may
initially appear complex, but it is just a repetition of an encoder-GAN. Meaning
that if we understood how to train one encoder-GAN, the rest uses the same concept.
In the following section, we assume that the StackedGAN is designed for the MNIST
digit generation:
Figure 6.2.2: A StackedGAN is made of a stack of an encoder and GAN. The encoder is pre-trained to
perform classification. Generator 1
, G 1
, learns to synthesize f 1f
features conditioned on the fake label, y f
, and
latent code, z 1f
. Generator 0
, G 0
, produces fake images using both the fake features, f 1f
and latent code, z 0f
.
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