Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

Abstract 3D-aware generative adversarial networks (GANs) synthesize high-fidelity and
multi-view-consistent facial images using only collections of single-view 2D imagery …

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 …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

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 …

Existing methods of 3D dthus limiting the scope of their practical applications. In this paper,
we propose a novel regression framework which makes a balance among speed, accuracy …

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 …

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 …