AI-generated content (AIGC) methods aim to produce text, images, videos, 3D assets, and
other media using AI algorithms. Due to its wide range of applications and the demonstrated …

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 …

The ability to create realistic animatable and relightable head avatars from casual video
sequences would open up wide ranging applications in communication and entertainment …

Recently, text-guided 3D generative methods have made remarkable advancements in
producing high-quality textures and geometry, capitalizing on the proliferation of large vision …

We propose FlashAvatar a novel and lightweight 3D animatable avatar representation that
could reconstruct a digital avatar from a short monocular video sequence in minutes and …

Talking head generation aims to generate faces that maintain the identity information of the
source image and imitate the motion of the driving image. Most pioneering methods rely …

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 …

In this paper, we present our method for neural face reenactment, called HyperReenact, that
aims to generate realistic talking head images of a source identity, driven by a target facial …

We present Follow-Your-Emoji, a diffusion-based framework for portrait animation, which
animates a reference portrait with target landmark sequences. The main challenge of portrait …

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 …