Monthly Archives: October 2020

Pengbin Tang, Jonas Zehnder, Stelian Coros, Bernhard Thomaszewski We present a computational method for designing compliant mechanical systems that exhibit large-amplitude oscillations. The technical core of our approach is an optimization-driven design tool that combines sensitivity analysis for optimization with … Continue reading →

Andreas Longva, Fabian Löschner, Tassilo Kugelstadt, José Antonio Fernández-Fernández, Jan Bender As demands for high-fidelity physics-based animations increase, the need for accurate methods for simulating deformable solids grows. While higher-order finite elements are commonplace in engineering due to their superior … Continue reading →

David A.B. Hyde, Steven W. Gagniere, Alan Marquez-Razon, Joseph Teran We present an updated Lagrangian discretization of surface tension forcesfor the simulation of liquids with moderate to extreme surface tension effects.The potential energy associated with surface tension is proportional to … Continue reading →

Zahra Forootaninia, Rahul Narain We propose a simple and efficient method for guiding an Eulerian smoke simulation to match the behavior of a specified velocity field, such as a low-resolution animation of the same scene, while preserving the rich, turbulent … Continue reading →

Xiao-Song Chen, Chen-Feng Li, Geng-Chen Cao, Yun-Tao Jiang and Shi-Min Hu In physically based-based animation, pure particle methods are popular due to their simple data structure, easy implementation, and convenient parallelization. As a pure particle-based method and using Galerkin discretization, … Continue reading →

Moritz Geilinger, David Hahn, Jonas Zehnder, Moritz Bächer, Bernhard Thomaszewski, Stelian Coros We present a differentiable dynamics solver that is able to handle fric-tional contact for rigid and deformable objects within a unified framework.Through a principled mollification of normal and … Continue reading →

Yuwei Xiao, Szeyu Chan, Siqi Wang, Bo Zhu, Xubo Yang Enabling adaptivity on a uniform Cartesian grid is challenging due to its highly structured grid cells and axis-aligned grid lines. In this paper, we propose a new grid structure – … Continue reading →

Ning Jin, Yilin Zhu, Zhenglin Geng, Ronald Fedkiw With the aim of creating virtual cloth deformations more similar to real world clothing, we propose a new computational framework that recasts three dimensional cloth deformation as an RGB image in a … Continue reading →

Raquel Vidaurre, Igor Santesteban, Elena Garces, Dan Casas We present a learning-based approach for virtual try-on applications based on a fully convolutional graph neural network. In contrast to existing data-driven models, which are trained for a specific garment or mesh … Continue reading →

Dieter Morgenroth, Stefan Reinhardt, Daniel Weiskopf, Bernhard Eberhardt We present a method to simulate fluid flow on evolving surfaces, e.g., an oil film on a water surface. Given an animated surface (e.g., extracted from a particle-based fluid simulation) in three-dimensional … Continue reading →