Faceswap Forum

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?

On the former, although I have not tested myself, the general consensus is that feeding FS with ML generated faces tends to not work out so well (there are artefacts in generated faces that we may not see, but the model definitely does). That being said, this should not dissuade you from experimenting and reporting back

The 2nd, yes... absolutely. I do similar. On projects where timings are tight for data collection, I will often 'pretrain' a model on known facesets I have, and then switch out the sources when the real data arrives.