Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation. (arXiv:2208.12550v1 [cs.CV])

3D-aware GANs based on generative neural radiance fields (GNeRF) have
achieved impressive high-quality image generation, while preserving strong 3D
consistency. The most notable achievements are made in the face generation
domain. However, most of these models focus on improving view consistency but
neglect a disentanglement aspect, thus these models cannot provide high-quality
semantic/attribute control over generation. To this end, we introduce a
conditional GNeRF model that uses specific attribute labels as input in order
to improve the controllabilities and disentangling …

3d arxiv cv face generation neural radiance fields training