Modeling and rendering photorealistic avatars is of crucial importance in many applications.
Existing methods that build a 3D avatar from visual observations, however, struggle to …

We present a self-supervised method to learn dynamic 3D deformations of garments worn
by parametric human bodies. State-of-the-art data-driven approaches to model 3D garment …

We propose a method that leverages graph neural networks, multi-level message passing,
and unsupervised training to enable real-time prediction of realistic clothing dynamics …

The realism of digital avatars is crucial in enabling telepresence applications with self-
expression and customization. While physical simulations can produce realistic motions for …

We present a new method for implicit time integration of physical systems. Our approach
builds a bridge between nodal Finite Element methods and Position Based Dynamics …

We propose a differentiable cloth simulator that can be embedded as a layer in deep neural
networks. This approach provides an effective, robust framework for modeling cloth …

Soft robots are primarily composed of soft materials that can allow for mechanically robust
maneuvers that are not typically possible with conventional rigid robotic systems. However …

The most popular approaches for the simulation of dynamic systems in computer graphics
are force based. Internal and external forces are accumulated from which accelerations are …

We present a technique for cloth simulation that dynamically refines and coarsens triangle
meshes so that they automatically conform to the geometric and dynamic detail of the …

We extend the incremental potential contact (IPC) model for contacting elastodynamics to
resolve systems composed of codimensional DOFs in arbitrary combination. This enables a …