Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

The computer graphics and vision communities have dedicated long standing efforts in
building computerized tools for reconstructing, tracking, and analyzing human faces based …

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

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient 2D face alignment and 3D face reconstruction in-the-wild remain an open …

We demonstrate that it is possible to perform face-related computer vision in the wild using
synthetic data alone. The community has long enjoyed the benefits of synthesizing training …

Recently, deep learning based 3D face reconstruction methods have shown promising
results in both quality and efficiency. However, training deep neural networks typically …

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 …

We propose a straightforward method that simultaneously reconstructs the 3D facial
structure and provides dense alignment. To achieve this, we design a 2D representation …

We present a novel approach that enables photo-realistic re-animation of portrait videos
using only an input video. In contrast to existing approaches that are restricted to …

Face recognition is one of the most important abilities that we use in our daily lives. There
are several reasons for the growing interest in automated face recognition, including rising …