Reconstructing 3D objects from a single image guided by pretrained diffusion models has
demonstrated promising outcomes. However, due to utilizing the case-agnostic rigid …

We present a one-shot method to infer and render a photorealistic 3D representation from a
single unposed image (eg, face portrait) in real-time. Given a single RGB input, our image …

Abstract 3D GAN inversion aims to achieve high reconstruction fidelity and reasonable 3D
geometry simultaneously from a single image input. However, existing 3D GAN inversion …

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 …

3D facial avatar reconstruction has been a significant research topic in computer graphics
and computer vision, where photo-realistic rendering and flexible controls over poses and …

Prior to the deep learning era, shape was commonly used to describe the objects.
Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly …

Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution
pre-estimated on the training set. An inaccurate estimation may mislead the model into …

This work presents 3DPE, a practical method that can efficiently edit a face image following
given prompts, like reference images or text descriptions, in a 3D-aware manner. To this …

Generating photorealistic 3D faces from given conditions is a challenging task. Existing
methods often rely on time-consuming one-by-one optimization approaches, which are not …

Our goal with this survey is to provide an overview of the state of the art deep learning
methods for face generation and editing using StyleGAN. The survey covers the evolution of …