Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing
the resolution of low-resolution (LR) face images to generate high-resolution face images, is …

Traditional 3D morphable face models (3DMMs) provide fine-grained control over
expression but cannot easily capture geometric and appearance details. Neural volumetric …

While current monocular 3D face reconstruction methods can recover fine geometric details,
they suffer several limitations. Some methods produce faces that cannot be realistically …

Abstract We present Neural Head Avatars, a novel neural representation that explicitly
models the surface geometry and appearance of an animatable human avatar that can be …

The fidelity of relighting is bounded by both geometry and appearance representations. For
geometry both mesh and volumetric approaches have difficulty modeling intricate structures …

Creating photorealistic avatars of existing people currently requires extensive person-
specific data capture, which is usually only accessible to the VFX industry and not the …

Face reconstruction and tracking is a building block of numerous applications in AR/VR,
human-machine interaction, as well as medical applications. Most of these applications rely …

Deep learning has been successfully applied to solve various complex problems ranging
from big data analytics to computer vision and human-level control. Deep learning advances …

Limited by the nature of the low-dimensional representational capacity of 3DMM, most of the
3DMM-based face reconstruction (FR) methods fail to recover high-frequency facial details …