StyleGAN is a deep learning generative model that produces high-resolution, photorealistic human faces. It introduces a style-based generator architecture that separates high-level attributes (pose, identity) from stochastic variations (freckles, hair) through progressive growing and style mixing. The model enables intuitive control over different aspects of the generated images at various scales.