Creating high-fidelity 3D head avatars has always been a research hotspot but there
remains a great challenge under lightweight sparse view setups. In this paper we propose …

Efficient generation of 3D digital humans is important in several industries including virtual
reality social media and cinematic production. 3D generative adversarial networks (GANs) …

Recent years have seen remarkable progress in deep learning powered visual content
creation. This includes deep generative 3D-aware image synthesis, which produces high …

Generating realistic 3D worlds occupied by moving humans has many applications in
games, architecture, and synthetic data creation. But generating such scenes is expensive …

We present a method that reconstructs and animates a 3D head avatar from a single-view
portrait image. Existing methods either involve time-consuming optimization for a specific …

The increased demand for 3D data in AR/VR robotics and gaming applications gave rise to
powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of these …

Generative models aim to learn the distribution of observed data by generating new
instances. With the advent of neural networks, deep generative models, including variational …

Existing approaches to animatable NeRF-based head avatars are either built upon face
templates or use the expression coefficients of templates as the driving signal. Despite the …

Various techniques have been developed and introduced to address the pressing need to
create three-dimensional (3D) content for advanced applications such as virtual reality and …

DiffusionAvatars synthesizes a high-fidelity 3D head avatar of a person offering intuitive
control over both pose and expression. We propose a diffusion-based neural renderer that …