“Nerf-based Generative models have shown impressive capacity in generating high-quality images with consistent 3D geometry. Despite successful synthesis of fake identity images randomly sampled from latent space, adopting these models for generating face images of real subjects is still a challenging task due to its so-called inversion issue. In this paper, we propose a universal method to surgically finetune these NeRF-GAN models in order to achieve high-fidelity animation of real subjects only by a single image.”

Find the paper and full list of authors in the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition proceedings.