How can you integrate GANs with VAEs for more robust image generation

Question

Is there any way to integrate GANs with VAEs for more robust image generation?

Answer 1

To Integrate GANs with VAEs, you can combine the generative capabilities of VAEs with the adversarial training of GANs to enhance image quality and diversity, which is implemented using adversarially trained VAEs (VAE-GAN), where a VAE generates images, and a GAN discriminator improves realism.

Here is the code reference:

Below code showing combine training:

In the above code, key steps include VAE for Generative Modeling, where Latent encoding and reconstruction are done; GAN Discriminator for Realism, which distinguishes real vs. reconstructed images, and Combined Losses, where VAE loss (reconstruction + KL divergence) and GAN loss are used.

Hence, by referring to the above, you integrate GANs with VAEs for more robust image generation.