Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …

The ability to detect users' emotions for the purpose of emotion engineering is currently one
of the main endeavors of machine learning in affective computing. Among the more common …

The locations of the fiducial facial landmark points around facial components and facial
contour capture the rigid and non-rigid facial deformations due to head movements and …

Primates recognize complex objects such as faces with remarkable speed and reliability.
Here, we reveal the brain's code for facial identity. Experiments in macaques demonstrate …

We introduce a deep appearance model for rendering the human face. Inspired by Active
Appearance Models, we develop a data-driven rendering pipeline that learns a joint …

This work presents a statistical recognition approach performing large vocabulary
continuous sign language recognition across different signers. Automatic sign language …

We present a novel method for constructing Variational Autoencoder (VAE). Instead of using
pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of …

With the increasing number of public available training data for face alignment, the
regression-based methods attracted much attention and have become the dominant …

We present a novel discriminative regression based approach for the Constrained Local
Models (CLMs) framework, referred to as the Discriminative Response Map Fitting (DRMF) …

The development of facial databases with an abundance of annotated facial data captured
under unconstrained'in-the-wild'conditions have made discriminative facial deformable …