- StyleGAN of all trades [1]
- StyleGANv1[5]
- StyleGANv2[6]: remove blob-shaped artifacts that resemble water droplets.
- StyleGANv3[2]: solve alias (texture sticking) issue, that is, detail appearing to glued to image coordinates instead of the surface of depicted objects.
- StyleGAN-XL [3]: extend to large dataset
- 3D styleGAN [4]
Image editing using styleGA
InsetGAN [7]
Reference
[1] Chong, Min Jin, Hsin-Ying Lee, and David Forsyth. “StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN.” arXiv preprint arXiv:2111.01619 (2021).
[2] Karras, Tero, et al. “Alias-free generative adversarial networks.” Thirty-Fifth Conference on Neural Information Processing Systems. 2021.
[3] Sauer, Axel, Katja Schwarz, and Andreas Geiger. “Stylegan-xl: Scaling stylegan to large diverse datasets.” arXiv preprint arXiv:2202.00273 (2022).
[4] Xiaoming Zhao, Fangchang Ma, David Güera, Zhile Ren, Alexander G. Schwing, Alex Colburn. “Generative Multiplane Images: Making a 2D GAN 3D-Aware”.
[5] Karras, Tero, Samuli Laine, and Timo Aila. “A style-based generator architecture for generative adversarial networks.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019.
[6] Karras, Tero, et al. “Analyzing and improving the image quality of stylegan.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020.
[7] Frühstück, Anna, et al. “Insetgan for full-body image generation.” CVPR, 2022.