My GANs is like this:
- Train an autoencoder (VAE), get the decoder part and use as Generator
- Train Discriminator
After training, do the generation in these steps:
- Call Generator to generate an image
- Call the Discriminator to classify the image to see whether it's acceptable
The problem is that the Discriminator says 'false' a lot, which means the generated image is not useful.
How should the Generator change (update weights) when Discriminator doesn't accept its generated image?