ISSN 1727-5288
Since 2018 full papers are published every two years as part of Computer Graphics Forum.

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  • Efficient acoustic perception for virtual AI agents 

    Chemistruck, Mike; Allen, Andrew; Snyder, John; Raghuvanshi, Nikunj (ACM, 2021)
    We model acoustic perception in AI agents efficiently within complex scenes with many sound events. The key idea is to employ perceptual parameters that capture how each sound event propagates through the scene to the ...
  • A GAN-Like Approach for Physics-Based Imitation Learning and Interactive Control 

    Xu, Pei; Karamouzas, Ioannis (ACM, 2021)
    We present a simple and intuitive approach for interactive control of physically simulated characters. Our work builds upon generative adversarial networks (GAN) and reinforcement learning, and introduces an imitation ...
  • Global Position Prediction for Interactive Motion Capture 

    Schreiner, Paul; Perepichka, Maksym; Lewis, Hayden; Darkner, Sune; Kry, Paul G.; Erleben, Kenny; Zordan, Victor B. (ACM, 2021)
    We present a method for reconstructing the global position of motion capture where position sensing is poor or unavailable. Capture systems, such as IMU suits, can provide excellent pose and orientation data of a capture ...
  • A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation 

    Daniel, Beatriz Cabrero; Marques, Ricardo; Hoyet, Ludovic; Pettré, Julien; Blat, Josep (ACM, 2021)
    Simulating crowds requires controlling a very large number of trajectories and is usually performed using crowd motion algorithms for which appropriate parameter values need to be found. The study of the relation between ...
  • Visual Simulation of Soil-Structure Destruction with Seepage Flows 

    Wang, Xu; Fujisawa, Makoto; Mikawa, Masahiko (ACM, 2021)
    This paper introduces a method for simulating soil-structure coupling with water, which involves a series of visual effects, including wet granular materials, seepage flows, capillary action between grains, and dam breaking ...
  • Neural UpFlow: A Scene Flow Learning Approach to Increase the Apparent Resolution of Particle-Based Liquids 

    Roy, Bruno; Poulin, Pierre; Paquette, Eric (ACM, 2021)
    We present a novel up-resing technique for generating high-resolution liquids based on scene flow estimation using deep neural networks. Our approach infers and synthesizes small- and large-scale details solely from a ...
  • Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry 

    Quigley, Ed; Lin, Winnie; Zhu, Yilin; Fedkiw, Ronald (ACM, 2021)
    We tackle the challenging problem of creating full and accurate three dimensional reconstructions of botanical trees with the topological and geometric accuracy required for subsequent physical simulation, e.g. in response ...
  • Recovering Geometric Information with Learned Texture Perturbations 

    Wu, Jane; Jin, Yongxu; Geng, Zhenglin; Zhou, Hui; Fedkiw, Ronald (ACM, 2021)
    Regularization is used to avoid overfitting when training a neural network; unfortunately, this reduces the attainable level of detail hindering the ability to capture high-frequency information present in the training ...
  • Flexible Motion Optimization with Modulated Assistive Forces 

    Kim, Nam Hee; Ling, Hung Yu; Xie, Zhaoming; Panne, Michiel Van De (ACM, 2021)
    Animated motions should be simple to direct while also being plausible. We present a flexible keyframe-based character animation system that generates plausible simulated motions for both physically-feasible and ...
  • Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model 

    Park, Soomin; Jang, Deok-Kyeong; Lee, Sung-Hee (ACM, 2021)
    This paper presents a novel deep learning-based framework for translating a motion into various styles within multiple domains. Our framework is a single set of generative adversarial networks that learns stylistic features ...
  • A functional skeleton transfer 

    Musoni, Pietro; Marin, Riccardo; Melzi, Simone; Castellani, Umberto (ACM, 2021)
    The animation community has spent significant effort trying to ease rigging procedures. This is necessitated because the increasing availability of 3D data makes manual rigging infeasible. However, object animations involve ...
  • Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control 

    Kugelstadt, Tassilo; Bender, Jan; Fernández-Fernández, José Antonio; Jeske, Stefan Rhys; Löschner, Fabian; Longva, Andreas (ACM, 2021)
    We develop a new operator splitting formulation for the simulation of corotated linearly elastic solids with Smoothed Particle Hydrodynamics (SPH). Based on the technique of Kugelstadt et al. [2018] originally developed ...
  • Volume Preserving Simulation of Soft Tissue with Skin 

    Sheen, Seung Heon; Larionov, Egor; Pai, Dinesh K. (ACM, 2021)
    Simulation of human soft tissues in contact with their environment is essential in many fields, including visual effects and apparel design. Biological tissues are nearly incompressible. However, standard methods employ ...
  • Coupling Friction with Visual Appearance 

    Andrews, Sheldon; Nassif, Loic; Erleben, Kenny; Kry, Paul G. (ACM, 2021)
    We present a novel meso-scale model for computing anisotropic and asymmetric friction for contacts in rigid body simulations that is based on surface facet orientations. The main idea behind our approach is to compute a ...
  • Issue Information 

    Narain, Rahul; Neff, Michael; Zordan, Victor (ACM, 2021)
    Table of Contents, Editors' Preface, and Author Index
  • Online Motion Synthesis Framework using a Simple Mass Model based on Predictive Coding 

    Hwang, Jaepyung; Ishii, Shin; Oba, Shigeyuki (ACM, 2019)
    Hybrid-based character animation utilizing the motion capture data and a simplified physics model allows synthesizing the motion data without losing its naturalness of the original motion. However, using both the physical ...
  • Human Articular Movement Algorithm to Simulate Muscle Contraction and Embedded Tissue Deformation 

    Atsumi, Noritoshi; Kato, Daichi; Hirabayashi, Satoko; Nakahira, Yuko; Iwamoto, Masami (ACM, 2019)
    The visualization of human articular movements associated with internal deformation is critical for many fields including biome- chanics. In this work, we present a novel algorithm to describe realistic articular movement ...
  • Interaction Motion Retargeting to Highly Dissimilar Furniture Environment 

    Jin, Taeil; Lee, Sung-Hee (ACM, 2019)
    Retageting a human-environment interaction motion to a different environment remains as an important research topic in computer animation. This paper introduces a novel method that can retarget an interaction motion to ...
  • Divergence-Free and Boundary-Respecting Velocity Interpolation Using Stream Functions 

    Chang, Jumyung; Azevedo, Vinicius C.; Batty, Christopher (ACM, 2019)
    In grid-based fluid simulation, discrete incompressibility of each cell is enforced by the pressure projection. However, pointwise velocities constructed by interpolating the discrete velocity samples from the staggered ...
  • Subspace Neural Physics: Fast Data-Driven Interactive Simulation 

    Holden, Daniel; Duong, Bang Chi; Datta, Sayantan; Nowrouzezahrai, Derek (ACM, 2019)
    Data-driven methods for physical simulation are an attractive option for interactive applications due to their ability to trade precomputation and memory footprint in exchange for improved runtime performance. Yet, existing ...

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