TY  - JOUR
TI  - A Style-Based Generator Architecture for GANs (StyleGAN)
AU  - Karras, T.
AU  - Laine, S.
AU  - Aila, T.
PY  - 2019
DA  - 2019///
JO  - CVPR 2019 (IEEE/CVF)
AB  - Karras, Laine and Aila (2019) redesigned the GAN generator to inject learned style vectors at each resolution level via adaptive instance normalisation, replacing the traditional input latent with a mapping network that produces a disentangled intermediate latent space. The architecture gives fine-grained independent control over coarse features such as pose and face shape, mid-level features such as hairstyle, and fine-detail features such as skin texture. StyleGAN set the benchmark for photorealistic synthetic face generation and became the reference architecture for generative character work in animation, games and digital-human pipelines. Its successors (StyleGAN2, StyleGAN3) and the latent-editing methods built on its intermediate space form a widely taught family in AI-art and character-generation courses.
KW  - generative-ai
KW  - image-generation
KW  - character-animation
UR  - https://arxiv.org/abs/1812.04948
LA  - en
ER  -