The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

We focus on reconstructing high-fidelity radiance fields of human heads, capturing their
animations over time, and synthesizing re-renderings from novel viewpoints at arbitrary time …

Abstract We present Monocular Neural Parametric Head Models (MonoNPHM) for dynamic
3D head reconstructions from monocular RGB videos. To this end we propose a latent …

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 …

Generating realistic human 3D reconstructions using image or video data is essential for
various communication and entertainment applications. While existing methods achieved …

The synthesis of 3D facial animations from speech has garnered considerable attention.
Due to the scarcity of high-quality 4D facial data and well-annotated abundant multi-modality …

We introduce FaceTalk a novel generative approach designed for synthesizing high-fidelity
3D motion sequences of talking human heads from input audio signal. To capture the …

Abstract 3D-aware Generative Adversarial Networks (GANs) have shown remarkable
progress in learning to generate multi-view-consistent images and 3D geometries of scenes …

The creation of high-fidelity, digital versions of human heads is an important stepping stone
in the process of further integrating virtual components into our everyday lives. Constructing …

Generating 3D models lies at the core of computer graphics and has been the focus of
decades of research. With the emergence of advanced neural representations and …