Sagan: Self-Attention Generative Adversarial Networks

Introduction:
In recent years, deep learning has made significant advancements in the field of generative models. One such model is the Self-Attention Generative Adversarial Network (Sagan). Sagan leverages the power of self-attention mechanisms to generate high-quality and coherent images. In this article, we will dive into the details of Sagan and explore its architecture and training process.

Sagan Architecture:
The Sagan architecture builds upon the traditional Generative Adversarial Network (GAN) framework by incorporating self-attention mechanisms. The key idea behind self-attention is to capture long-range dependencies between different spatial locations within an image. This allows the generator to focus on important regions and generate more realistic and de