In recent years, researchers have proposed many deep learning (DL) methods for various
tasks, and particularly face recognition (FR) made an enormous leap using these …

In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as
3D geometric information provides more discriminative features. This comprehensive survey …

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

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 …

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 …

Three-dimensional (3D) face recognition has been extensively investigated in the last two
decades due to its wide range of applications in many areas, such as security and forensics …

In this paper, we introduce a real-time face recognition (and announcement) system targeted
at aiding the blind and low-vision people. The system uses a Microsoft Kinect sensor as a …

As face recognition progresses from constrained scenarios to unconstrained scenarios, new
challenges such as large pose, bad illumination, and partial occlusion, are encountered …

With the increasing availability of consumer depth sensors, 3D face recognition (FR) has
attracted more and more attention. However, the data acquired by these sensors are often …

Due to the intrinsic invariance to pose and illumination changes, 3D Face Recognition (FR)
has a promising potential in the real world. 3D FR using high-quality faces, which are of high …