Comments (2)
Hi
No need to find new semantic directions. All the editing methods such as InterfaceGAN, GANSpace, StyleCLIP and more are working the same.
The editing directions that I have uploaded were trained on the pretrained StyleGAN, without PTI.
The key idea is that the fine-tuning happens on the already similar image to the input image.
As it turns out, this enables the fine-tuning to make small changes in its weights. Thus altering only appearance-related weights.
Furtheremore, the regularizaion forces the weight change to happen only in local region not affecting other identities.
To summarize, PTI is orthogonal to any editing method. If an editing method works on the pretrained StyleGAN, it will work on the personalized StyleGAN after PTI.
from pti.
Got it.
Thanks!
from pti.
Related Issues (20)
- The more smile, the more black HOT 5
- How did you find the directions? HOT 1
- Unexpected size of W features in generated_images = self.G.synthesis(w, noise_mode='const', force_fp32=True) HOT 2
- opt multi image one time? HOT 1
- The input parameters of the Generator HOT 1
- checkpoint HOT 3
- SG and SG2 issue HOT 2
- GPU error HOT 1
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- Failed to run 512x512 images
- How to improve the invert image to be more similar to the input image? HOT 1
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from pti.