Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

As 3D facial avatars become more widely used for communication, it is critical that they
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …

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 …

We present dynamic neural radiance fields for modeling the appearance and dynamics of a
human face. Digitally modeling and reconstructing a talking human is a key building-block …

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 …

StyleGAN generates photorealistic portrait images of faces with eyes, teeth, hair and context
(neck, shoulders, background), but lacks a rig-like control over semantic face parameters …

Abstract We propose Neural-DynamicReconstruction (NDR), a template-free method to
recover high-fidelity geometry and motions of a dynamic scene from a monocular RGB-D …

In this work we propose a novel model-based deep convolutional autoencoder that
addresses the highly challenging problem of reconstructing a 3D human face from a single …

We present a method for training a regression network from image pixels to 3D morphable
model coordinates using only unlabeled photographs. The training loss is based on features …