Portrait Synthesis

Portrait synthesis focuses on generating realistic and editable images of human faces, aiming for high fidelity, 3D consistency across viewpoints, and fine-grained control over features like pose, expression, and even individual facial parts. Current research heavily utilizes generative adversarial networks (GANs), particularly StyleGAN variants, often coupled with neural radiance fields (NeRFs) for 3D-aware generation and manipulation. This field is significant for its applications in virtual avatars, video conferencing, and entertainment, while also advancing our understanding of face representation and manipulation within computer vision and graphics.