Generative models have been in existence for many decades. In the field of machine
learning, we come across many scenarios when directly learning a target is intractable …

As one of the most comprehensive and objective ways to describe facial expressions, the
Facial Action Coding System (FACS) has recently received significant attention. Over the …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

One of the main challenges in feature learning using Deep Convolutional Neural Networks
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …

As a classic statistical model of 3D facial shape and texture, 3D Morphable Model (3DMM) is
widely used in facial analysis, eg, model fitting, image synthesis. Conventional 3DMM is …

Embedding 3D morphable basis functions into deep neural networks opens great potential
for models with better representation power. However, to faithfully learn those models from …

As a classic statistical model of 3D facial shape and albedo, 3D Morphable Model (3DMM) is
widely used in facial analysis, eg, model fitting, image synthesis. Conventional 3DMM is …

We present a deep learning-based technique to infer high-quality facial reflectance and
geometry given a single unconstrained image of the subject, which may contain partial …

Deep neural networks (DNNs) trained on large-scale datasets have recently achieved
impressive improvements in face recognition. But a persistent challenge remains to develop …

Facial alignment involves finding a set of landmark points on an image with a known
semantic meaning. However, this semantic meaning of landmark points is often lost in 2D …