October 2018
Intermediate to advanced
368 pages
9h 20m
English
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. Generator1, G1, learns to synthesize f1f features conditioned on the fake label, ...