Many successful models for scene or object recognition transform low-level descriptors
(such as Gabor filter responses, or SIFT descriptors) into richer representations of …

Reconstructing the detailed geometric structure of a face from a given image is a key to
many computer vision and graphics applications, such as motion capture and reenactment …

We address the issues of 3-D head pose estimation and face modeling from a depth image.
Given a depth image, random forests are effective for estimating the location and orientation …

Reconstructing 3D facial geometry from a single RGB image has recently instigated wide
research interest. However, it is still an ill-posed problem and most methods rely on prior …

Muscle-based systems have the potential to provide both anatomical accuracy and semantic
interpretability as compared to blendshape models; however, a lack of expressivity and …

This study explores the potential of a fully convolutional mesh autoencoder model for
regenerating 3D nature faces with the presence of imperfect areas. We utilize deep learning …

We consider the problem of depth-based robust 3D facial pose tracking under
unconstrained scenarios with heavy occlusions and arbitrary facial expression variations …

We address the issue of 3D face modeling and tracking from RGB-D images. Existing
methods usually fit a deformable model to an RGB-D image using iterative closest point …

In this work, we present a new method for 3D face reconstruction from sparse‐view RGB
images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with …

In this paper, we propose a generative framework that unifies depth-based 3D facial pose
tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy …