We explore learning a native generative model for 360° full head from limited 3D head data. Three key problems are studied: 1) utilizing various representations for 360°-renderable head generation; 2) disentangling face appearance, shape, and motion for editable and motion-driven 3D head models; 3) enhancing model generalization for downstream tasks.
arXiv 2024