While current monocular 3D face reconstruction methods can recover fine geometric details,
they suffer several limitations. Some methods produce faces that cannot be realistically …

To facilitate the analysis of human actions, interactions and emotions, we compute a 3D
model of human body pose, hand pose, and facial expression from a single monocular …

We present a statistical, articulated 3D human shape modeling pipeline, within a fully
trainable, modular, deep learning framework. Given high-resolution complete 3D body …

Learned 3D representations of human faces are useful for computer vision problems such
as 3D face tracking and reconstruction from images, as well as graphics applications such …

We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically
constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the …

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 …

Abstract We present Large Scale Facial Model (LSFM)--a 3D Morphable Model (3DMM)
automatically constructed from 9,663 distinct facial identities. To the best of our knowledge …

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

While existing methods for 3D face reconstruction from in-the-wild images excel at
recovering the overall face shape they commonly miss subtle extreme asymmetric or rarely …

Three-dimensional morphable models (3DMMs) are powerful statistical tools for
representing the 3D shapes and textures of an object class. Here we present the most …