Recently, a lot of attention has been focused on the incorporation of 3D data into face
analysis and its applications. Despite providing a more accurate representation of the face …

Recently, deep learning based 3D face reconstruction methods have shown promising
results in both quality and efficiency. However, training deep neural networks typically …

Heatmap regression with a deep network has become one of the mainstream approaches to
localize facial landmarks. However, the loss function for heatmap regression is rarely …

The 3D shapes of faces are well known to be discriminative. Yet despite this, they are rarely
used for face recognition and always under controlled viewing conditions. We claim that this …

Recent learning-based approaches, in which models are trained by single-view images
have shown promising results for monocular 3D face reconstruction, but they suffer from the …

Despite recent advances in face recognition using deep learning, severe accuracy drops are
observed for large pose variations in unconstrained environments. Learning pose-invariant …

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 …

In this article, we provide a detailed survey of 3D Morphable Face Models over the 20 years
since they were first proposed. The challenges in building and applying these models …

Large-pose face alignment is a very challenging problem in computer vision, which is used
as a prerequisite for many important vision tasks, eg, face recognition and 3D face …

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 …