# Generative Adversarial Network

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.

Avatar is a simple web application that can help users randomly generate avatars in different styles. The application offers various avatar forms, including half-body, sitting, and standing poses, which users can choose according to their preferences. The application uses generative adversarial network (GAN) technology to output high-quality, detail-rich avatar images. Compared to traditional avatar creation methods, it is more convenient and quick, and it can produce more personalized avatars. Overall, it is a practical and interesting web application suitable for various scenarios requiring avatars.

Neuroid is an AI-powered 3D modeling and animation generation tool that enables users to transform their creative ideas into complex 3D models and animations with simple and efficient operations, thereby enhancing creativity and productivity. Leveraging the powerful capabilities of Generative Adversarial Networks, Neuroid revolutionizes the field of 3D motion design. It can analyze large datasets, learn various motion patterns, and unlock unprecedented creativity and efficiency for designers in the process of motion design.

Stable Diffusion XL (SDXL) is a generative adversarial network (GAN) model that can generate expressive images with shorter prompts and insert text into images. It is an improved version of the Stable Diffusion model developed by Stability AI, resulting in higher quality and more controllable image generation, and supporting localized image editing with natural language. This model can be used for various creative design tasks, such as concept art, graphic design, video effects, and more.

Drag Your GAN is a tool for interactive point manipulation of generative adversarial networks (GANs). It allows you to precisely control the pose, shape, expression, and layout of generated images by dragging points on the image. With Drag Your GAN, you can manipulate images of various categories, such as animals, cars, humans, and landscapes. These manipulations are performed on the learned image generation manifold, resulting in realistic outputs even in challenging scenarios (such as phantom content occlusion and maintaining object rigid shape deformation). Drag Your GAN outperforms previous methods in image manipulation and point tracking tasks.

Drag Your GAN is an interactive point-based Generative Adversarial Network (GAN) tool for image manipulation. It allows users to precisely manipulate the pose, shape, expression, and layout of images by dragging points within the image. The tool achieves this through two main components: 1) Feature-based motion supervision, which guides the movement of points towards their target positions; 2) A novel point tracking method that utilizes discriminator GAN features to continuously locate the positions of points. Users can manipulate a variety of image categories, including animals, vehicles, people, and landscapes. By operating within the learned image space of the GAN, the tool produces realistic outputs capable of handling challenging scenarios, such as generating occluded content and maintaining object shape coherence. Drag Your GAN outperforms existing methods in image manipulation and point tracking tasks while also demonstrating the ability to manipulate real images through GAN inversion.