258 citations · 449 across the 15 of their papers we have counts for
15 papers
Learning a Generalized Physical Face Model From Data
Lingchen Yang, Gaspard Zoss, Prashanth Chandran +4
Physically-based simulation is a powerful approach for 3D facial animation as the resulting deformations are governed by physical constraints, allowing to easily resolve self-colli…
An Implicit Physical Face Model Driven by Expression and Style
Lingchen Yang, Gaspard Zoss, Prashanth Chandran +5
3D facial animation is often produced by manipulating facial deformation models (or rigs), that are traditionally parameterized by expression controls. A key component that is usua…
Implicit Neural Representation for Physics-driven Actuated Soft Bodies
Lingchen Yang, Byungsoo Kim, Gaspard Zoss +3
Active soft bodies can affect their shape through an internal actuation mechanism that induces a deformation. Similar to recent work, this paper utilizes a differentiable, quasi-st…
Efficient Incremental Potential Contact for Actuated Face Simulation
Bo Li, Lingchen Yang, Barbara Solenthaler
We present a quasi-static finite element simulator for human face animation. We model the face as an actuated soft body, which can be efficiently simulated using Projective Dynamic…
Spatially Adaptive Cloth Regression with Implicit Neural Representations
Lei Shu, Vinicius Azevedo, Barbara Solenthaler +1
The accurate representation of fine-detailed cloth wrinkles poses significant challenges in computer graphics. The inherently non-uniform structure of cloth wrinkles mandates the e…
Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision
Aleksandra Franz, Barbara Solenthaler, Nils Thuerey
We address the challenging problem of jointly inferring the 3D flow and volumetric densities moving in a fluid from a monocular input video with a deep neural network. Despite the…