Open legion-s opened 2 years ago
zzzucf
commented
1 year ago "I can not spot visible artifacts for the generated images", me too. Please advise.
I download the pytorch version of stylegan and use Nvidia FFHQ pretrained model to generate 10,000 images. After running the 'compute_statistics.py', I observed a very smooth spectrum without any artifacts.
516396859
commented
1 year ago Poor generalization, waste of time
Joool
commented
1 year ago I download the pytorch version of stylegan and use Nvidia FFHQ pretrained model to generate 10,000 images. After running the 'compute_statistics.py', I observed a very smooth spectrum without any artifacts.
The original plots where made using the tensorflow version of StyleGAN I1). PyTorch might implement the upsampling techniques differently (see https://openaccess.thecvf.com/content/CVPR2022/html/Parmar_On_Aliased_Resizing_and_Surprising_Subtleties_in_GAN_Evaluation_CVPR_2022_paper.html).
BTW just because humans cannot see differences anymore, this does not mean that classifiers do not find it useful. Several newer works still use similar techniques (https://ojs.aaai.org/index.php/AAAI/article/view/19954).
Joool
commented
1 year ago Poor generalization, waste of time
The paper is three years old at this stage. Obviously newer models have adapted. See for example StyleGAN3 which specifically addressed upsampling problems..
Firstly，in the 'README.md' file, you note FFHQ is distributed in a cropped version, how to crop FFHQ image？Can you give me a code to process it. Secondly，when i use ‘compute_statistics.py’ file to generate DCT spectrum of a data set sampled from StyleGAN trained on FFHQ，i can not spot visible artifacts for the generated images. I don't know if there is something wrong with me，can you give me some advice？