In-Domain GAN Inversion for Real Image Editing
Based on Seonghyeon Kim's Pytorch Implementation of StyleGAN2
[Paper] [Official Code] [StyleGAN2 Pytorch]
Train Encoder
python train_encoder.py
0k iter
1M iter
[encoder checkpoint] [generator checkpoint]
Note: The encoder architecture and loss weights are different from the original implemetation.
Interpolation
interpolate.ipynb
Domain-Guided Encoder (Initial projection)
In-Domain Inversion (500 steps)
Inperpolation Result
Encoder + Model Interpolation
