Los Angeles, California | July 2017
Posters

Papers I: SPH Fluids
Density Maps for Improved SPH Boundary Handling
Dan Koschier and Jan Bender
Fully Asynchronous SPH Simulation
Stefan Reinhardt, Markus Huber, Bernhard Eberhardt, and Daniel Weiskopf
Evaporation and Condensation of SPH-based Fluids
Hendrik Hochstetter and Andreas Kolb
A Micropolar Material Model for Turbulent SPH Fluids
Jan Bender, Dan Koschier, Tassilo Kugelstadt, and Marcel Weiler
Papers II: Fluids
Physically-Based Droplet Interaction
Richard Jones and Richard Southern
Hierarchical Vorticity Skeletons
Sebastian Eberhardt, Steffen Weissmann, Ulrich Pinkall, and Nils Thuerey
A Positive-Definite Cut-Cell Method for Strong Two-Way Coupling Between Fluids and Deformable Bodies
Omar Zarifi and Christopher Batty
Papers III: Kinematic Characters
Authoring Motion Cycles
Loïc Ciccone, Martin Guay, Maurizio Nitti, and Robert W. Sumner
Emotion Control of Unstructured Dance Movements
Andreas Aristidou, Qiong Zeng, Efstathios Stavrakis, KangKang Yin, Daniel Cohen-Or, Yiorgos Chrysanthou, and Baoquan Chen
Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks
Samuli Laine, Tero Karras, Timo Aila, Antti Herva, Shunsuke Saito, Ronald Yu, Hao Li, and Jaakko Lehtinen
Papers IV: Physics-Based Characters
Augmenting Sampling Based Controllers with Machine Learning
Joose Rajamäki and Perttu Hämäläinen
Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter?
Xue Bin Peng and Michiel van de Panne
Papers V: Rigid Bodies, Chains & Trees
Rigid Body Contact Problems using Proximal Operators
Kenny Erleben
Long Range Constraints for Rigid Body Simulations
Matthias Müller, Nuttapong Chentanez, Miles Macklin, and Stefan Jeschke
Designing Cable-Driven Actuation Networks for Kinematic Chains and Trees
Vittorio Megaro, Espen Knoop, Andrew Spielberg, David I.W. Levin, Wojciech Matusik, Markus Gross, Bernhard Thomaszewski, and Moritz Bächer
Papers VI: Cloth
Inequality Cloth
Ning Jin, Wenlong Lu, Zhenglin Geng, and Ronald P. Fedkiw
Modeling and Data-Driven Parameter Estimation for Woven Fabrics
David Clyde, Joseph Teran, and Rasmus Tamstorf

Recent Submissions

  • Modeling and Data-Driven Parameter Estimation for Woven Fabrics 

    Clyde, David; Teran, Joseph; Tamstorf, Rasmus (ACM, 2017)
    Accurate estimation of mechanical parameters for simulation of woven fabrics is essential in many fields. To facilitate this we first present a new orthotropic hyperelastic constitutive model for woven fabrics. Next, we ...
  • Inequality Cloth 

    Jin, Ning; Lu, Wenlong; Geng, Zhenglin; Fedkiw, Ronald P. (ACM, 2017)
    As has been noted and discussed by various authors, numerical simulations of deformable bodies often adversely suffer from so-called ''locking'' artifacts. We illustrate that the ''locking'' of out-of-plane bending motion ...
  • Designing Cable-Driven Actuation Networks for Kinematic Chains and Trees 

    Megaro, Vittorio; Knoop, Espen; Spielberg, Andrew; Levin, David I.W.; Matusik, Wojciech; Gross, Markus; Thomaszewski, Bernhard; Bächer, Moritz (ACM, 2017)
    In this paper we present an optimization-based approach for the design of cable-driven kinematic chains and trees. Our system takes as input a hierarchical assembly consisting of rigid links jointed together with hinges. ...
  • Long Range Constraints for Rigid Body Simulations 

    Müller, Matthias; Chentanez, Nuttapong; Macklin, Miles; Jeschke, Stefan (ACM, 2017)
    The two main constraints used in rigid body simulations are contacts and joints. Both constrain the motion of a small number of bodies in close proximity. However, it is often the case that a series of constraints restrict ...
  • Rigid Body Contact Problems using Proximal Operators 

    Erleben, Kenny (ACM, 2017)
    Iterative methods are popular for solving contact force problems in rigid body dynamics. They are loved for their robustness and surrounded by mystery as to whether they converge or not. We provide a mathematical foundation ...
  • Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter? 

    Peng, Xue Bin; Panne, Michiel van de (ACM, 2017)
    The use of deep reinforcement learning allows for high-dimensional state descriptors, but little is known about how the choice of action representation impacts learning and the resulting performance. We compare the impact ...
  • Augmenting Sampling Based Controllers with Machine Learning 

    Rajamäki, Joose; Hämäläinen, Perttu (ACM, 2017)
    E cient learning of 3D character control still remains an open problem despite of the remarkable recent advances in the field. We propose a new algorithm that combines planning by a samplingbased model-predictive controller ...
  • Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks 

    Laine, Samuli; Karras, Tero; Aila, Timo; Herva, Antti; Saito, Shunsuke; Yu, Ronald; Li, Hao; Lehtinen, Jaakko (ACM, 2017)
    We present a real-time deep learning framework for video-based facial performance capture-the dense 3D tracking of an actor's face given a monocular video. Our pipeline begins with accurately capturing a subject using a ...
  • Emotion Control of Unstructured Dance Movements 

    Aristidou, Andreas; Zeng, Qiong; Stavrakis, Efstathios; Yin, KangKang; Cohen-Or, Daniel; Chrysanthou, Yiorgos; Chen, Baoquan (ACM, 2017)
    Motion capture technology has enabled the acquisition of high quality human motions for animating digital characters with extremely high fidelity. However, despite all the advances in motion editing and synthesis, it remains ...
  • Authoring Motion Cycles 

    Ciccone, Loïc; Guay, Martin; Nitti, Maurizio; Sumner, Robert W. (ACM, 2017)
    Motion cycles play an important role in animation production and game development. However, creating motion cycles relies on general-purpose animation packages with complex interfaces that require expert training. Our work ...
  • A Positive-Definite Cut-Cell Method for Strong Two-Way Coupling Between Fluids and Deformable Bodies 

    Zarifi, Omar; Batty, Christopher (ACM, 2017)
    We present a new approach to simulation of two-way coupling between inviscid free surface fluids and deformable bodies that exhibits several notable advantages over previous techniques. By fully incorporating the dynamics ...
  • Hierarchical Vorticity Skeletons 

    Eberhardt, Sebastian; Weissmann, Steffen; Pinkall, Ulrich; Thuerey, Nils (ACM, 2017)
    We propose a novel method to extract hierarchies of vortex filaments from given three-dimensional flow velocity fields. We call these collections of filaments Hierarchical Vorticity Skeletons (HVS). They extract multi-scale ...
  • Physically-Based Droplet Interaction 

    Jones, Richard; Southern, Richard (ACM, 2017)
    In this paper we present a physically-based model for simulating realistic interactions between liquid droplets in an e cient manner. Our particle-based system recreates the coalescence, separation and fragmentation ...
  • A Micropolar Material Model for Turbulent SPH Fluids 

    Bender, Jan; Koschier, Dan; Kugelstadt, Tassilo; Weiler, Marcel (ACM, 2017)
    In this paper we introduce a novel micropolar material model for the simulation of turbulent inviscid fluids. The governing equations are solved by using the concept of Smoothed Particle Hydrodynamics (SPH). As already ...
  • Evaporation and Condensation of SPH-based Fluids 

    Hochstetter, Hendrik; Kolb, Andreas (ACM, 2017)
    In this paper we present a method to simulate evaporation and condensation of liquids. Therefore, both the air and liquid phases have to be simulated. We use, as a carrier of vapor, a coarse grid for the air phase and ...
  • Fully Asynchronous SPH Simulation 

    Reinhardt, Stefan; Huber, Markus; Eberhardt, Bernhard; Weiskopf, Daniel (ACM, 2017)
    We present a novel method for fully asynchronous time integration of particle-based fluids using smoothed particle hydrodynamics (SPH). With our approach, we allow a dedicated time step for each particle. Therefore, we are ...
  • Density Maps for Improved SPH Boundary Handling 

    Koschier, Dan; Bender, Jan (ACM, 2017)
    In this paper, we present the novel concept of density maps for robust handling of static and rigid dynamic boundaries in fluid simulations based on Smoothed Particle Hydrodynamics (SPH). In contrast to the vast majority ...