Why does my GAN produce a blurry image instead of sharp realistic ones

Question

With the help of code examples, can you explain to me why my GAN produces a blurry image instead of sharp, realistic ones?

Answer 1

To address this, use techniques like using a deeper discriminator, improving the generator architecture, or applying techniques like Wasserstein loss.

Here is the code reference you can refer to:

In the above code, we are using the following:

• Wasserstein Loss: Using Wasserstein loss helps stabilize GAN training, leading to sharper and more realistic images.
• Improved Discriminator: A more powerful discriminator helps the model distinguish between real and fake data better, reducing blurriness.
• Better Architecture: Consider using deeper networks or advanced architectures like DCGANs to improve image quality.

Hence, by referring to the above, you can produce a blurry image instead of a sharp realistic one.