Update (2020/10/28)
Release checkpoints of StyleGAN fine-tuned on cat and dog datasets.
Update (2020/04/06)
Current code evaluates FID scores with inception.train() mode. Fixing it to inception.eval() may degrade the overall scores (both competitors and ours; hence the trend does not change). Thanks to @jychoi118 (Issue #3) for reporting this.
Official code for "Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs" (CVPRW 2020).
The code is heavily based on the StyleGAN-pytorch and SNGAN-projection-chainer codes.
See stylegan and projection directory for StyleGAN and SNGAN-projection experiments, respectively.
Note: There is a bug in PyTorch 1.4.0, hence one should use torch>=1.5.0 or torch<=1.3.0. See Issue #1.
Generated samples over fine-tuning FFHQ-pretrained StyleGAN
Generated samples under Animal Face and Anime Face datasets
Comparison of fine-tuning (left) and freeze D (right) under Oxford Flower, CUB-200-2011, and Caltech-256 datasets
Freeze D generates more class-consistent results (see row 2, 8 of Oxford Flower)
If you use this code for your research, please cite our papers.
@inproceedings{
mo2020freeze,
title={Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs},
author={Mo, Sangwoo and Cho, Minsu and Shin, Jinwoo},
booktitle = {CVPR AI for Content Creation Workshop},
year={2020},
}