How do you implement self-attention layers in GANs to generate high-quality images with fine details

Question

Can you tell me How to implement self-attention layers in GANs to generate high-quality images with fine details?

Answer 1

To implement self-attention layers in GANs for generating high-quality images with fine details, you add a Self-Attention Module (e.g., SAGAN-style) to capture long-range dependencies and enhance detail generation. Here is the code you can refer to:

In the above code, we using the following:

• Self-Attention Module:

  • Captures global dependencies and spatial relationships in the image.
  • Enhances fine details and overall coherence.

• Placement:

  • Add self-attention layers at multiple resolutions within the generator.

• Gamma Parameter:

  • Controls the influence of attention. Initialized to 0 for residual learning.

• GAN Improvements:

  • Boosts high-quality detail generation in datasets with complex textures or diverse features.

Hence, you can implement self-attention layers in GANs to generate high-quality images with fine details