MiniFace

MiniFace is a research project and software tool developed by researchers at Carnegie Mellon University. Its primary purpose is to facilitate the creation of personalized 3D facial avatars from a single 2D photograph. The system aims to capture key facial features and expressions to generate a realistic and customizable digital representation of a person.

The technology behind MiniFace leverages deep learning techniques and computer vision algorithms. By analyzing the input image, MiniFace can infer depth information, reconstruct facial geometry, and map textures to create a plausible 3D model. This process allows for the generation of avatars that can be animated and used in various applications, such as virtual reality, augmented reality, and gaming.

MiniFace is particularly noted for its ability to generate avatars with a good degree of similarity to the original person, even from limited input. The project has been presented at academic conferences and is available as open-source software, encouraging further research and development in the field of facial reconstruction and avatar generation. The ongoing work focuses on improving accuracy, expressiveness, and the ease of use of the system.