Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …

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

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 …

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

This paper investigates the task of 2D human whole-body pose estimation, which aims to
localize dense landmarks on the entire human body including face, hands, body, and feet …

With the growth of online social network platforms and applications, large amounts of textual
user-generated content are created daily in the form of comments, reviews, and short-text …

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a
novel algorithm that is able to predict elaborate riggable 3D face models from a single image …

We present FaceVerse, a fine-grained 3D Neural Face Model, which is built from hybrid East
Asian face datasets containing 60K fused RGB-D images and 2K high-fidelity 3D head scan …

Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

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 …