TriPlaneNet: An Encoder for EG3D Inversion

Understand

Recent progress in NeRF-based GANs has introduced a number of approaches for high-resolution and high-fidelity generative modeling of human heads with a possibility for novel view rendering.

• At the same time, one must solve an inverse problem to be able to re-render or modify an existing image or video.
• Despite the success of universal optimization-based methods for 2D GAN inversion, those applied to 3D GANs may fail to extrapolate the result onto the novel view, whereas optimization-based 3D GAN inversion methods are time-consuming and can require at least several minutes per image.
• Fast encoder-based techniques, such as those developed for StyleGAN, may also be less appealing due to the lack of identity preservation.