A close look on Paper "Few-shot Knowledge Transfer for Fine-grained Cartoon Face Generation"

Few-shot Knowledge Transfer for Fine-grained Cartoon Face Generation

Basic model

As mentioned above, we first train an image translation model with fX0;Y0g. Some unsupervised methods like CycleGAN [24], UNIT [15] are all suitable.

Here we utilize an open source project for its impressive performance, which is modified from U-GAT-IT[13].

In this project, a face-ID loss are introduced to further improve the performance in response to faces. More details can be found on the project homepage.

The open-source project they used:

minivision-ai/photo2cartoon

https://s3-us-west-2.amazonaws.com/secure.notion-static.com/b0cc9529-7472-4a96-9240-0857283a5d51/Untitled.png

https://s3-us-west-2.amazonaws.com/secure.notion-static.com/03621854-8f8e-435a-a41f-d7abbb461d69/Untitled.png

Related Paper - U-GAT-IT

https://s3-us-west-2.amazonaws.com/secure.notion-static.com/17d9db6a-6c92-4433-baa3-444faa845c42/Untitled.png

What I learned

  1. Compare other technologies/techniques/Models on the performance & final results