GGHead is a 3D Generative Adversarial Network (GAN) based on 3D Gaussian scattering representation, designed to learn 3D head priors from a collection of 2D images. This technology simplifies the prediction process by leveraging the regularity of the UV space of template head meshes to predict a set of 3D Gaussian attributes. Key advantages of GGHead include high efficiency, high-resolution generation, full 3D consistency, and real-time rendering capabilities. It enhances the geometric fidelity of generated 3D heads through a novel total variation loss, ensuring that neighboring rendered pixels originate from close Gaussian points in UV space.