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

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 …

Recent advancements in deep learning and computer vision have led to a surge of interest
in generating realistic talking heads. This paper presents a comprehensive survey of state-of …

Generative deep learning techniques have invaded the public discourse recently. Despite
the advantages, the applications to disinformation are concerning as the counter-measures …

In this paper, we propose Generalizable and Animatable Gaussian head Avatar
(GAGAvatar) for one-shot animatable head avatar reconstruction. Existing methods rely on …

Despite the great progress of deep learning and generative adversarial networks, face
frontalization (ie, profile-to-frontal synthesis) and profile (ie, non-frontal) face recognition still …

Recently, neural radiance fields have made significant advancements in rendering new
views. However, limited research has focused on dynamically loading implicit radiance …

The widespread application of face recognition technology has exacerbated privacy threats.
Face de-identification is an effective means of protecting visual privacy by concealing …