With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

The quality and size of training set have a great impact on the results of deep learning-
based face-related tasks. However, collecting and labeling adequate samples with high …

Despite previous success in generating audio-driven talking heads, most of the previous
studies focus on the correlation between speech content and the mouth shape. Facial …

The synthesis of natural emotional reactions is an essential criterion in vivid talking-face
video generation. This criterion is nevertheless seldom taken into consideration in previous …

We propose a novel generative adversarial network (GAN) for the task of unsupervised
learning of 3D representations from natural images. Most generative models rely on 2D …

The recent proliferation of fake portrait videos poses direct threats on society, law, and
privacy [1]. Believing the fake video of a politician, distributing fake pornographic content of …

The objective of this paper is a neural network model that controls the pose and expression
of a given face, using another face or modality (eg audio). This model can then be used for …

Recently, emotional talking face generation has received considerable attention. However,
existing methods only adopt one-hot coding, image, or audio as emotion conditions, thus …

The creation or manipulation of facial appearance through deep generative approaches,
known as DeepFake, have achieved significant progress and promoted a wide range of …

Abstract Automatic Facial Expression Recognition (FER) has attracted increasing attention
in the last 20 years since facial expressions play a central role in human communication …