So I had a thought about the possibility of building and training a GAN model for generating more "faces" for a limited "face" dataset.
The model would learn on the limited dataset and also the landmarks of the faces. Then, we would ask the model to provide different faces based on different landmark configurations/shapes.
Perhaps an additional large dataset of a well-known face that has many different landmark configurations would also be beneficial to be pre-trained on and frozen or something similar.
This is all new to me but has anyone else had any similar ideas or even implemented such a thing? How feasible would it actually be - and of course - is it really worth the effort?