In recent years, methods for image generation have exploded giving birth to many applications. At the same time, digital avatars have become increasingly popular in social networks. Thus, we see a big opportunity to use generative networks to improve and automatize avatar creation.
To explore methods like GANs and VAEs to create digital avatars, being able to specify their general style as well as their specific features. This will make them more similar to the people they are intended to resemble, and could even automatize their creation from real life pictures.
Datasets to use: CelebA, Google facial expression comparison dataset, YouTube Faces Dataset with Facial Keypoints.
Since both the software techniques and avatar creation are relatively new topics, this work can then be improved and extended to the many applications into which these topics will grow.