Human performance capture is a highly important computer vision problem with many
applications in movie production and virtual/augmented reality. Many previous performance …

Many anatomical factors, such as bone geometry and muscle condition, interact to affect
human movements. This work aims to build a comprehensive musculoskeletal model and its …

Great progress has been made in estimating 3D human pose and shape from images and
video by training neural networks to directly regress the parameters of parametric human …

We present the first real-time human performance capture approach that reconstructs dense,
space-time coherent deforming geometry of entire humans in general everyday clothing …

We address the problem of inferring the anatomic skeleton of a person, in an arbitrary pose,
from the 3D surface of the body; ie we predict the inside (bones) from the outside (skin). This …

Many of the actions that we take with our hands involve self-contact and occlusion: shaking
hands, making a fist, or interlacing our fingers while thinking. This use of of our hands …

We present a novel physics-based approach to facial animation. Contrary to commonly used
generative methods, our solution computes facial expressions by minimizing a set of non …

Emerging Metaverse applications demand reliable, accurate, and photorealistic
reproductions of human hands to perform sophisticated operations as if in the physical …

We present SoftSMPL, a learning‐based method to model realistic soft‐tissue dynamics as a
function of body shape and motion. Datasets to learn such task are scarce and expensive to …

Creating metrically accurate avatars is important for many applications such as virtual
clothing try-on, ergonomics, medicine, immersive social media, telepresence, and gaming …