Comments (2)
Hi @koojagyum!
All 4 editing techniques displayed in the paper (InterFaceGAN, GANSpace, SeFa, and StyleFlow) can be used to edit face images after their inversion into a W(k,*) 18x512 latent code (Using the e4e encoder for example).
Other then InterFaceGAN, we did not train GANSpace, SeFa, or StyleFlow for additional editing directions, meaning we used the existing capabilities of each technique.
To train InterFaceGAN, you can use their official repository, but you need to sample many w(,) [1x512 style vector] vectors and obtain matching labels for each of the images produced by the style vector (you can read more about it at their official repository).
Edit:
Mabe This Issue can help.
from encoder4editing.
Thanks for your clear answer and comment.
Actually, I tried gender editing using stylegan2-distillation, and it worked somehow.
And even StyleGAN-v1 boundaries from InterFaceGAN also worked.
from encoder4editing.
Related Issues (20)
- is it possible to fine tune? HOT 2
- Resume training for cars
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- Inference with sample size >1 fails HOT 1
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- Error while running inference.py HOT 2
- Training e4e for 512*256 stylegan HOT 2
- Regarding finding directions in W+ space
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from encoder4editing.