AI-Assisted Pipeline for 3D Face Avatar Generation

Filling virtual environments with realistic-looking avatars is essential for games, film production, and virtual reality. Creating a fun and engaging experience requires a wide variety of different-looking avatars. There are two main methods to create realistic-looking avatars. One is to scan a real person's face using a light room. The second is for the artist/designer to create the avatar manually using advanced tools. Both of these approaches are expensive in terms of time, computing, and human labour. This thesis leverages generative models like Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) to automate avatar creation. Our pipeline offers control over three aspects: face shape, skin color, and fine details like beards or wrinkles. This provides artists flexibility in avatar creation and can integrate with tools like MOSAR for controlling avatars from 2D images.