STYLEGAN Procedure
References
Karnewar, A., and Wang, O. (2020). “MSG-GAN: Multi-scale Gradients for Generative Adversarial Networks.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2020/papers/Karnewar_MSG-GAN_Multi-Scale_Gradients_for_Generative_Adversarial_Networks_CVPR_2020_paper.pdf.
Karras, T., Aila, T., Laine, S., and Lehtinen, J. (2018). “Progressive Growing of GANs for Improved Quality, Stability, and Variation.” In Proceedings of the Sixth International Conference on Learning Representations. La Jolla, CA: ICLR. https://openreview.net/pdf?id=Hk99zCeAb.
Karras, T., Laine, S., and Aila, T. (2019). “A Style-Based Generator Architecture for Generative Adversarial Networks.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2019/papers/Karras_A_Style-Based_Generator_Architecture_for_Generative_Adversarial_Networks_CVPR_2019_paper.pdf.
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., and Aila, T. (2020). “Analyzing and Improving the Image Quality of StyleGAN.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2020/papers/Karras_Analyzing_and_Improving_the_Image_Quality_of_StyleGAN_CVPR_2020_paper.pdf.
Kingma, D. P., and Ba, J. (2015). “Adam: A Method for Stochastic Optimization.” In Proceedings of the 3rd International Conference for Learning Representations. Baixas, France: ISCA. https://arxiv.org/abs/1412.6980.