10 citations · 20 across the 4 of their papers we have counts for
4 papers
Joint Learning of Depth and Appearance for Portrait Image Animation
Xinya Ji, Gaspard Zoss, Prashanth Chandran +4
2D portrait animation has experienced significant advancements in recent years. Much research has utilized the prior knowledge embedded in large generative diffusion models to enha…
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…
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…