Monthly Archives: July 2024

Xuan Li, Minchen Li, Xuchen Han, Huamin Wang, Yin Yang, Chenfanfu Jiang This paper presents a novel method to couple Finite Element Methods (FEM), typically employed for modeling Lagrangian solids such as flesh, cloth, hair, and rigid bodies, with Material … Continue reading →

Xing Shen, Runyuan Cai, Mengxiao Bi Tangjie Lv The linear conjugate gradient method is widely used in physical simulation, particularly for solving large-scale linear systems derived from Newton’s method. The nonlinear conjugate gradient method generalizes the conjugate gradient method to … Continue reading →

Yushan Han, Yizhou Chen, Carmichael Ong, Jingyu Chen, Jennifer Hicks, Joseph Teran We present a comprehensive neural network to model the deformation of human soft tissues including muscle, tendon, fat and skin. Our approach provides kinematic and active correctives to … Continue reading →

Marcelo Martins, Lucas Morais, Rafael Torchelsen, Luciana Nedel, Anderson Maciel Current endoscopy simulators oversimplify navigation and interaction within tubular anatomical structures to maintain interactive frame rates, neglecting the intricate dynamics of permanent contact between the organ and the medical tool. … Continue reading →

Vismay Modi, Nicholas Sharp, Or Perel, Shinjiro Sueda, David I. W. Levin The proliferation of 3D representations, from explicit meshes to implicit neural fields and more, motivates the need for simulators agnostic to representation. We present a data-, mesh-, and … Continue reading →

Yizhou Chen, Yushan Han, Jingyu Chen, Zhan Zhang, Alex Mcadams, Joseph Teran Position based dynamics [Müller et al. 2007] is a powerful technique for simulating a variety of materials. Its primary strength is its robustness when run with limited computational … Continue reading →

Artur Grigorev, Giorgio Becherini, Michael Black, Otmar Hilliges, Bernhard Thomaszewski Learning-based approaches to cloth simulation have started to show their potential in recent years. However, handling collisions and intersections in neural simulations remains a largely unsolved problem. In this work, … Continue reading →

Yixin Chen, David I.W. Levin, Timothy R. Langlois Physics-based fluid control has long been a challenging problem in balancing efficiency and accuracy. We introduce a novel physicsbased fluid control pipeline using Laplacian Eigenfluids. Utilizing the adjoint method with our provided … Continue reading →

Ningxiao Tao, Liangwang Ruan , Yitong Deng, Bo Zhu, Bin Wang, Baoquan Chen This paper introduces a novel physically-based vortex fluid model for films, aimed at accurately simulating cascading vortical structures on deforming thin films. Central to our approach is … Continue reading →

Zhongtian Zheng, Tongtong Wang, Qijia Feng, Zherong Pan, Xifeng Gao, Kui Wu Simulating high-resolution cloth poses computational challenges in real-time applications. In the gaming industry, the proxy mesh technique offers an alternative, simulating a simplified low-resolution cloth geometry, proxy mesh. … Continue reading →