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Advanced Deep Learning with Keras
book

Advanced Deep Learning with Keras

by Rowel Atienza, Neeraj Verma, Valerio Maggio
October 2018
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 20m
English
Packt Publishing
Content preview from Advanced Deep Learning with Keras

The CycleGAN Model

Figure 7.1.3 shows the network model of the CycleGAN. The objective of the CycleGAN is to learn the function:

y' = G(x) (Equation 7.1.1)

That generates fake images, y ', in the target domain as a function of the real source image, x. Learning is unsupervised by capitalizing only on the available real images, x, in the source domain and real images, y, in the target domain.

Unlike regular GANs, CycleGAN imposes the cycle-consistency constraint. The forward cycle-consistency network ensures that the real source data can be reconstructed from the fake target data:

x' = F(G(x)) (Equation 7.1.2)

This is done by minimizing the forward cycle-consistency L1 loss:

(Equation 7.1.3)

The network is symmetric. The backward cycle-consistency ...

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Publisher Resources

ISBN: 9781788629416Supplemental Content