Filters








1,991 Hits in 5.4 sec

Neural Implicit Surfaces for Efficient and Accurate Collisions in Physically Based Simulations [article]

Hugo Bertiche, Meysam Madadi, Sergio Escalera
2021 arXiv   pre-print
We propose using implicit surface representations learnt through deep learning for collision handling in physically based simulations.  ...  We will show how this permits accurate and efficient collision handling in physically based simulations, more specifically, for cloth. In our experiments, we query up to 1M points in 300 milliseconds.  ...  We demonstrated how it is possible to use them for efficient and accurate collision handling in physically based simulations.  ... 
arXiv:2110.01614v1 fatcat:cmgyuw3h7rgalaxfolavnoblhu

From early virtual garment simulation to interactive fashion design

Pascal Volino, Frederic Cordier, Nadia Magnenat-Thalmann
2005 Computer-Aided Design  
Virtual garment design and simulation involves a combination of a large range of techniques, involving mechanical simulation, collision detection, and user interface techniques for creating garments.  ...  The framework integrates innovative tools aimed towards efficiency and quality in the process of garment design and prototyping, taking advantage of state-of-the-art algorithms from the field of mechanical  ...  Thanks to Marlène Arévalo and Christiane Luible for their design work to the garment models illustrating this paper.  ... 
doi:10.1016/j.cad.2004.09.003 fatcat:imqn6gum3ncahhnv4roqji5iya

Deep Medial Fields [article]

Daniel Rebain, Ke Li, Vincent Sitzmann, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi
2021 arXiv   pre-print
Working in unison with the O(1) surface projection supported by the SDF, the medial field opens the door for an entirely new set of efficient, shape-aware operations on implicit representations.  ...  rigid-body collision proxies, and an efficient approximation of ambient occlusion that remains stable with respect to viewpoint variations.  ...  ACKNOWLEDGMENTS The authors would like to thank Brian Wyvill, Frank Dellaert, and Ryan Schmidt for their helpful comments.  ... 
arXiv:2106.03804v1 fatcat:fgchknabinhztnmb6t2qmkqnxm

Neural Collision Detection for Deformable Objects [article]

Ryan S. Zesch, Bethany R. Witemeyer, Ziyan Xiong, David I.W. Levin, Shinjiro Sueda
2022 arXiv   pre-print
We propose a neural network-based approach for collision detection with deformable objects.  ...  We demonstrate our approach with two concrete examples: a haptics application with a finite element mesh, and cloth simulation with a skinned character.  ...  Our neural approach to collision detection has none of these limitations and can be readily deployed for collision detection in deformable physics simulations.  ... 
arXiv:2202.02309v1 fatcat:czrgtbk2pvexze3grkqbextz4i

Key Techniques for interactive Virtual Garment Simulation [article]

Pascal Volino, Nadia Magnenat-Thalmann, Bernhard Thomaszewski, Markus Wacker
2005 Eurographics State of the Art Reports  
Virtual garment design and simulation involves a combination of a large range of techniques, involving mechanical simulation, collision detection, and user interface techniques for creating garments.  ...  CAD techniques for the garment industry.  ...  The neural network is trained with a set of samples that have been computed with the physically based method. Not surprisingly, their simulator works in real-time.  ... 
doi:10.2312/egt.20051053 fatcat:yfpy6t5y6rhtvjwedgldfr3l7i

Data-Driven Approach to Simulating Realistic Human Joint Constraints [article]

Yifeng Jiang, C. Karen Liu
2018 arXiv   pre-print
The paper introduces a new technique to accurately simulate human joint limits in physics simulation.  ...  The function in the implicit equation is represented by a fully connected neural network whose gradients can be efficiently computed via back-propagation.  ...  For example, we can create a dynamic constraint to enforce the learned joint limits in a physics simulator.  ... 
arXiv:1709.08685v2 fatcat:4akxamliajaydkxnrrxzvpwq2m

Full-Body Visual Self-Modeling of Robot Morphologies [article]

Boyuan Chen, Robert Kwiatkowski, Carl Vondrick, Hod Lipson
2021 arXiv   pre-print
In physical experiments, we demonstrate how a visual self-model is accurate to about one percent of the workspace, enabling the robot to perform various motion planning and control tasks.  ...  Such query-driven self models are continuous in the spatial domain, memory efficient, fully differentiable and kinematic aware.  ...  In total, we collected 10,000 data points in simulation with PyBullet (6) and 7,888 data points in the physical setup.  ... 
arXiv:2111.06389v2 fatcat:g4teepszo5emdgs32qrlop3cuq

Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On

Igor Santesteban, Nils Thuerey, Miguel A. Otaduy, Dan Casas
2021 Zenodo  
Key to our success is a new canonical space for garments that removes pose-and-shape deformations already captured by a new diffused human body model, which extrapolates body surface properties such as  ...  We propose a new generative model for 3D garment deformations that enables us to learn, for the first time, a data-driven method for virtual try-on that effectively addresses garment-body collisions.  ...  Related Work Current approaches to animate 3D clothing can be classified into: physics-based simulation and data-driven models. Physics-Based Cloth Simulation.  ... 
doi:10.5281/zenodo.5595961 fatcat:tmku2entezbpla2cpk2guuxqja

Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On [article]

Igor Santesteban, Nils Thuerey, Miguel A. Otaduy, Dan Casas
2021 arXiv   pre-print
Key to our success is a new canonical space for garments that removes pose-and-shape deformations already captured by a new diffused human body model, which extrapolates body surface properties such as  ...  We propose a new generative model for 3D garment deformations that enables us to learn, for the first time, a data-driven method for virtual try-on that effectively addresses garment-body collisions.  ...  The work was also funded in part by the European Research Council (ERC Consolidator Grant no. 772738 TouchDesign) and Spanish Ministry of Science (RTI2018-098694-B-I00 VizLearning).  ... 
arXiv:2105.06462v1 fatcat:qrwso7qfcfh5pg4yv46wsspjx4

Deep Physics-aware Inference of Cloth Deformation for Monocular Human Performance Capture [article]

Yue Li, Marc Habermann, Bernhard Thomaszewski, Stelian Coros, Thabo Beeler, Christian Theobalt
2021 arXiv   pre-print
To address these problems, we propose a person-specific, learning-based method that integrates a simulation layer into the training process to provide for the first time physics supervision in the context  ...  This leads to noticeable artifacts in their reconstructions, e.g. baked-in wrinkles, implausible deformations that seemingly defy gravity, and intersections between cloth and body.  ...  Acknowledgments The authors would like to thank the anonymous reviewers for their valuable feedback, and Gereon Fox for the video narration.  ... 
arXiv:2011.12866v2 fatcat:unwkgbplznatfjr2t66zt644dq

Taking visual motion prediction to new heightfields

Sebastien Ehrhardt, Aron Monszpart, Niloy J. Mitra, Andrea Vedaldi
2019 Computer Vision and Image Understanding  
In this work, we investigate if neural networks can implicitly learn physical states of real-world mechanical processes only based on visual data while internally modeling non-homogeneous environment and  ...  We develop a recurrent neural network architecture for this task and also characterize resultant uncertainties in the form of evolving variance estimates.  ...  Acknowledgments The authors would like to gratefully acknowledge the support of ERC DFR01600 and ERC SmartGeometry StG-2013-335373 grants.  ... 
doi:10.1016/j.cviu.2019.02.005 fatcat:ejnw44muoffafkqf2cvqunghwa

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact [article]

Yifei Li, Tao Du, Kui Wu, Jie Xu, Wojciech Matusik
2021 arXiv   pre-print
We draw inspiration from previous work to propose a fast and novel method for deriving gradients in PD-based cloth simulation with dry frictional contact.  ...  Our differentiable simulator extends a state-of-the-art cloth simulator based on Projective Dynamics (PD) and with dry frictional contact.  ...  Unlike penalty-based methods, constraint-based collision handling methods formulate contact as constraints in the physics system.  ... 
arXiv:2106.05306v2 fatcat:3a4wvzlf2rcprmz3k2ycmtc3kq

Training neural networks under physical constraints using a stochastic augmented Lagrangian approach [article]

Alp Dener, Marco Andres Miller, Randy Michael Churchill, Todd Munson, Choong-Seock Chang
2020 arXiv   pre-print
We investigate the physics-constrained training of an encoder-decoder neural network for approximating the Fokker-Planck-Landau collision operator in the 5-dimensional kinetic fusion simulation in XGC.  ...  accuracy than training with a fixed penalty method for our application problem, with the accuracy high enough for practical applications in kinetic simulations.  ...  the collision operator in the XGC simulation.  ... 
arXiv:2009.07330v1 fatcat:ea27twvsqzetpajvvyp2zephre

PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation [article]

Hugo Bertiche, Meysam Madadi, Sergio Escalera
2021 arXiv   pre-print
To the best of our knowledge, we are the first to propose a neural simulator for cloth. While deep-based approaches in the domain are becoming a trend, these are data-hungry models.  ...  Classical approaches rely on Physically Based Simulations (PBS) to animate clothes.  ...  This work has been partially supported by the Spanish project PID2019-105093GB-I00 (MINECO/FEDER, UE) and CERCA Programme/Generalitat de Catalunya.)  ... 
arXiv:2012.11310v3 fatcat:al6gzeekfza6rpnl37vwj5lzta

Deep-learning enhancement of large scale numerical simulations [article]

Caspar van Leeuwen, Damian Podareanu, Valeriu Codreanu, Maxwell X. Cai, Axel Berg, Simon Portegies Zwart, Robin Stoffer, Menno Veerman, Chiel van Heerwaarden, Sydney Otten, Sascha Caron, Cunliang Geng (+2 others)
2020 arXiv   pre-print
Our goal is to provide concrete guidelines to scientists and others that would like to explore opportunities for applying deep learning approaches in their own large-scale numerical simulations.  ...  Traditional simulations on High-Performance Computing (HPC) systems typically involve modeling very large domains and/or very complex equations.  ...  Sutskever and G. E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks," NIPS, 2012.  ... 
arXiv:2004.03454v1 fatcat:l4vs2ham6ngdjdvio66uieb5my
« Previous Showing results 1 — 15 out of 1,991 results