3D GAN Inversion

3D GAN inversion aims to reconstruct a 3D model from a single 2D image by mapping the image into the latent space of a 3D Generative Adversarial Network (GAN). Current research focuses on improving the fidelity and efficiency of this process, often employing encoder-based methods or optimization techniques to achieve high-quality 3D reconstructions, particularly using architectures like EG3D and PanoHead. These advancements enable applications such as realistic facial attribute editing, selfie undistortion, and the creation of animatable 3D avatars from images or videos, impacting fields like computer graphics, virtual reality, and digital content creation.