39-Issue 2

Permanent URI for this collection

Fluids
Asynchronous Eulerian Liquid Simulation
Tatsuya Koike, Shigeo Morishima, and Ryoichi Ando
Local Bases for Model-reduced Smoke Simulations
Olivier Mercier and Derek Nowrouzezahrai
Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions
Junyu Lai, Yangang Chen, Yu Gu, Christopher Batty, and Justin W. L. Wan
Point Clouds
Persistence Analysis of Multi-scale Planar Structure Graph in Point Clouds
Thibault Lejemble, Claudio Mura, Loïc Barthe, and Nicolas Mellado
Progressive Real-Time Rendering of One Billion Points Without Hierarchical Acceleration Structures
Markus Schütz, Gottfried Mandlburger, Johannes Otepka, and Michael Wimmer
Simulation of Soft Materials
SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans
Igor Santesteban, Elena Garces, Miguel A. Otaduy, and Dan Casas
Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars
Cristian Romero, Miguel A. Otaduy, Dan Casas, and Jesús Pérez
A Practical Method for Animating Anisotropic Elastoplastic Materials
Camille Schreck and Chris Wojtan
Mixing Yarns and Triangles in Cloth Simulation
Juan J. Casafranca, Gabriel Cirio, Alejandro Rodríguez, Eder Miguel, and Miguel A. Otaduy
Sparse Voxels and Texture Synthesis
Interactively Modifying Compressed Sparse Voxel Representations
Victor Careil, Markus Billeter, and Elmar Eisemann
UV-free Texturing using Sparse Voxel DAGs
Dan Dolonius, Erik Sintorn, and Ulf Assarsson
Deep Learning for Rendering
Spherical Gaussian Light-field Textures for Fast Precomputed Global Illumination
Roc Ramon Currius, Dan Dolonius, Ulf Assarsson, and Erik Sintorn
Neural Temporal Adaptive Sampling and Denoising
Jon Hasselgren, Jacob Munkberg, Marco Salvi, Anjul Patney, and Aaron Lefohn
DeepBRDF: A Deep Representation for Manipulating Measured BRDF
Bingyang Hu, Jie Guo, Yanjun Chen, Mengtian Li, and Yanwen Guo
Unified Neural Encoding of BTFs
Gilles Rainer, Abhijeet Ghosh, Wenzel Jakob, and Tim Weyrich
Geometry Processing
Combinatorial Construction of Seamless Parameter Domains
Jiaran Zhou, Changhe Tu, Denis Zorin, and Marcel Campen
Greedy Cut Construction for Parameterizations
Tianyu Zhu, Chunyang Ye, Shuangming Chai, and Xiao-Ming Fu
Locally Supported Tangential Vector, n-Vector, and Tensor Fields
Ahmad Nasikun, Christopher Brandt, and Klaus Hildebrandt
Faces
Expression Packing: As-Few-As-Possible Training Expressions for Blendshape Transfer
Emma Carrigan, Eduard Zell, Cedric Guiard, and Rachel McDonnell
Facial Expression Synthesis using a Global-Local Multilinear Framework
Mengjiao Wang, Derek Bradley, Stefanos Zafeiriou, and Thabo Beeler
Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems
Marco Fratarcangeli, Derek Bradley, Aurel Gruber, Gaspard Zoss, and Thabo Beeler
Optimizing Structures, Layouts, and Interactions
Invertible Paradoxic Loop Structures for Transformable Design
Zijia Li, Georg Nawratil, Florian Rist, and Michael Hensel
Interactive Modeling of Cellular Structures on Surfaces with Application to Additive Manufacturing
Pascal Stadlbauer, Daniel Mlakar, Hans-Peter Seidel, Markus Steinberger, and Rhaleb Zayer
Illumination-Guided Furniture Layout Optimization
Nick Vitsas, Georgios Papaioannou, Anastasios Gkaravelis, and Andreas-Alexandros Vasilakis
Meshes and Subdivision
Polygon Laplacian Made Simple
Astrid Bunge, Philipp Herholz, Misha Kazhdan, and Mario Botsch
Spectral Mesh Simplification
Thibault Lescoat, Hsueh-Ti Derek Liu, Jean-Marc Thiery, Alec Jacobson, Tamy Boubekeur, and Maks Ovsjanikov
Fast and Robust QEF Minimization using Probabilistic Quadrics
Philip Trettner and Leif Kobbelt
Subdivision-Specialized Linear Algebra Kernels for Static and Dynamic Mesh Connectivity on the GPU
Daniel Mlakar, Martin Winter, Pascal Stadlbauer, Hans-Peter Seidel, Markus Steinberger, and Rhaleb Zayer
Ray Tracing and Global Illumination
Stratified Markov Chain Monte Carlo Light Transport
Adrien Gruson, Rex West, and Toshiya Hachisuka
An Efficient Transport Estimator for Complex Layered Materials
Luis E. Gamboa, Adrien Gruson, and Derek Nowrouzezahrai
Spectral Mollification for Bidirectional Fluorescence
Alisa Jung, Johannes Hanika, and Carsten Dachsbacher
Optimization for Fabrication
Fast and Robust Stochastic Structural Optimization
Qiaodong Cui, Timothy Langlois, Pradeep Sen, and Theodore Kim
Computational Design and Optimization of Non-Circular Gears
Hao Xu, Tianwen Fu, Peng Song, Mingjun Zhou, Chi-Wing Fu, and Niloy J. Mitra
Designing Robotically-Constructed Metal Frame Structures
Zhao Ma, Alexander Walzer, Christian Schumacher, Romana Rust, Fabio Gramazio, Matthias Kohler, and Moritz Bächer
Optimizing Object Decomposition to Reduce Visual Artifacts in 3D Printing
Irene Filoscia, Thomas Alderighi, Daniela Giorgi, Luigi Malomo, Marco Callieri, and Paolo Cignoni
Images and Videos
Prefilters for Sharp Image Display
Luís Cláudio Gouveia Rocha, Manuel M. Oliveira, and Eduardo S. L. Gastal
RGB2AO: Ambient Occlusion Generation from RGB Images
Naoto Inoue, Daichi Ito, Yannick Hold-Geoffroy, Long Mai, Brian Price, and Toshihiko Yamasaki
Single Sensor Compressive Light Field Video Camera
Saghi Hajisharif, Ehsan Miandji, Christine Guillemot, and Jonas Unger
Accurate Real-time 3D Gaze Tracking Using a Lightweight Eyeball Calibration
Quan Wen, Derek Bradley, Thabo Beeler, Seonwook Park, Otmar Hilliges, Jun-Hai Yong, and Feng Xu
Synthesizing Gestures, Motion, and Interactions
Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows
Simon Alexanderson, Gustav Eje Henter, Taras Kucherenko, and Jonas Beskow
Motion Retargetting based on Dilated Convolutions and Skeleton-specific Loss Functions
SangBin Kim, Inbum Park, Seongsu Kwon, and JungHyun Han
Spatial Queries
Binary Ostensibly-Implicit Trees for Fast Collision Detection
Floyd M. Chitalu, Christophe Dubach, and Taku Komura
Real-time Anticipation of Occlusions for Automated Camera Control in Toric Space
Ludovic Burg, Christophe Lino, and Marc Christie
Efficient Minimum Distance Computation for Solids of Revolution
Sang-Hyun Son, Seung-Hyun Yoon, Myung-Soo Kim, and Gershon Elber
Segment Tracing Using Local Lipschitz Bounds
Eric Galin, Eric Guérin, Axel Paris, and Adrien Peytavie
Shape Collections
Robust Shape Collection Matching and Correspondence from Shape Differences
Aharon Cohen and Mirela Ben-Chen
Simulation of Fractures, Skyscapes, and Dendritic Paintings
Displacement-Correlated XFEM for Simulating Brittle Fracture
Floyd M. Chitalu, Qinghai Miao, Kartic Subr, and Taku Komura
Interactive Meso-scale Simulation of Skyscapes
Ulysse Vimont, James Gain, Maud Lastic, Guillaume Cordonnier, Babatunde Abiodun, and Marie-Paule Cani
Simulation of Dendritic Painting
José A. Canabal, Miguel A. Otaduy, Byungmoon Kim, and Jose Echevarria

BibTeX (39-Issue 2)
                
@article{
10.1111:cgf.13956,
journal = {Computer Graphics Forum}, title = {{
EUROGRAPHICS 2020: CGF 39-2 Frontmatter}},
author = {
Assarsson, Ulf
and
Panozzo, Daniele
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13956}
}
                
@article{
10.1111:cgf.13907,
journal = {Computer Graphics Forum}, title = {{
Asynchronous Eulerian Liquid Simulation}},
author = {
Koike, Tatsuya
and
Morishima, Shigeo
and
Ando, Ryoichi
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13907}
}
                
@article{
10.1111:cgf.13908,
journal = {Computer Graphics Forum}, title = {{
Local Bases for Model-reduced Smoke Simulations}},
author = {
Mercier, Olivier
and
Nowrouzezahrai, Derek
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13908}
}
                
@article{
10.1111:cgf.13909,
journal = {Computer Graphics Forum}, title = {{
Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions}},
author = {
Lai, Junyu
and
Chen, Yangang
and
Gu, Yu
and
Batty, Christopher
and
Wan, Justin W. L.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13909}
}
                
@article{
10.1111:cgf.13910,
journal = {Computer Graphics Forum}, title = {{
Persistence Analysis of Multi-scale Planar Structure Graph in Point Clouds}},
author = {
Lejemble, Thibault
and
Mura, Claudio
and
Barthe, Loïc
and
Mellado, Nicolas
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13910}
}
                
@article{
10.1111:cgf.13911,
journal = {Computer Graphics Forum}, title = {{
Progressive Real-Time Rendering of One Billion Points Without Hierarchical Acceleration Structures}},
author = {
Schütz, Markus
and
Mandlburger, Gottfried
and
Otepka, Johannes
and
Wimmer, Michael
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13911}
}
                
@article{
10.1111:cgf.13912,
journal = {Computer Graphics Forum}, title = {{
SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans}},
author = {
Santesteban, Igor
and
Garces, Elena
and
Otaduy, Miguel A.
and
Casas, Dan
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13912}
}
                
@article{
10.1111:cgf.13913,
journal = {Computer Graphics Forum}, title = {{
Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars}},
author = {
Romero, Cristian
and
Otaduy, Miguel A.
and
Casas, Dan
and
Pérez, Jesús
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13913}
}
                
@article{
10.1111:cgf.13914,
journal = {Computer Graphics Forum}, title = {{
A Practical Method for Animating Anisotropic Elastoplastic Materials}},
author = {
Schreck, Camille
and
Wojtan, Chris
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13914}
}
                
@article{
10.1111:cgf.13915,
journal = {Computer Graphics Forum}, title = {{
Mixing Yarns and Triangles in Cloth Simulation}},
author = {
Casafranca, Juan J.
and
Cirio, Gabriel
and
Rodríguez, Alejandro
and
Miguel, Eder
and
Otaduy, Miguel A.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13915}
}
                
@article{
10.1111:cgf.13916,
journal = {Computer Graphics Forum}, title = {{
Interactively Modifying Compressed Sparse Voxel Representations}},
author = {
Careil, Victor
and
Billeter, Markus
and
Eisemann, Elmar
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13916}
}
                
@article{
10.1111:cgf.13917,
journal = {Computer Graphics Forum}, title = {{
UV-free Texturing using Sparse Voxel DAGs}},
author = {
Dolonius, Dan
and
Sintorn, Erik
and
Assarsson, Ulf
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13917}
}
                
@article{
10.1111:cgf.13918,
journal = {Computer Graphics Forum}, title = {{
Spherical Gaussian Light-field Textures for Fast Precomputed Global Illumination}},
author = {
Currius, Roc Ramon
and
Dolonius, Dan
and
Assarsson, Ulf
and
Sintorn, Erik
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13918}
}
                
@article{
10.1111:cgf.13919,
journal = {Computer Graphics Forum}, title = {{
Neural Temporal Adaptive Sampling and Denoising}},
author = {
Hasselgren, Jon
and
Munkberg, Jacob
and
Salvi, Marco
and
Patney, Anjul
and
Lefohn, Aaron
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13919}
}
                
@article{
10.1111:cgf.13920,
journal = {Computer Graphics Forum}, title = {{
DeepBRDF: A Deep Representation for Manipulating Measured BRDF}},
author = {
Hu, Bingyang
and
Guo, Jie
and
Chen, Yanjun
and
Li, Mengtian
and
Guo, Yanwen
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13920}
}
                
@article{
10.1111:cgf.13921,
journal = {Computer Graphics Forum}, title = {{
Unified Neural Encoding of BTFs}},
author = {
Rainer, Gilles
and
Ghosh, Abhijeet
and
Jakob, Wenzel
and
Weyrich, Tim
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13921}
}
                
@article{
10.1111:cgf.13922,
journal = {Computer Graphics Forum}, title = {{
Combinatorial Construction of Seamless Parameter Domains}},
author = {
Zhou, Jiaran
and
Tu, Changhe
and
Zorin, Denis
and
Campen, Marcel
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13922}
}
                
@article{
10.1111:cgf.13923,
journal = {Computer Graphics Forum}, title = {{
Greedy Cut Construction for Parameterizations}},
author = {
Zhu, Tianyu
and
Ye, Chunyang
and
Chai, Shuangming
and
Fu, Xiao-Ming
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13923}
}
                
@article{
10.1111:cgf.13924,
journal = {Computer Graphics Forum}, title = {{
Locally Supported Tangential Vector, n-Vector, and Tensor Fields}},
author = {
Nasikun, Ahmad
and
Brandt, Christopher
and
Hildebrandt, Klaus
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13924}
}
                
@article{
10.1111:cgf.13925,
journal = {Computer Graphics Forum}, title = {{
Expression Packing: As-Few-As-Possible Training Expressions for Blendshape Transfer}},
author = {
Carrigan, Emma
and
Zell, Eduard
and
Guiard, Cedric
and
McDonnell, Rachel
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13925}
}
                
@article{
10.1111:cgf.13926,
journal = {Computer Graphics Forum}, title = {{
Facial Expression Synthesis using a Global-Local Multilinear Framework}},
author = {
Wang, Mengjiao
and
Bradley, Derek
and
Zafeiriou, Stefanos
and
Beeler, Thabo
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13926}
}
                
@article{
10.1111:cgf.13927,
journal = {Computer Graphics Forum}, title = {{
Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems}},
author = {
Fratarcangeli, Marco
and
Bradley, Derek
and
Gruber, Aurel
and
Zoss, Gaspard
and
Beeler, Thabo
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13927}
}
                
@article{
10.1111:cgf.13928,
journal = {Computer Graphics Forum}, title = {{
Invertible Paradoxic Loop Structures for Transformable Design}},
author = {
Li, Zijia
and
Nawratil, Georg
and
Rist, Florian
and
Hensel, Michael
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13928}
}
                
@article{
10.1111:cgf.13929,
journal = {Computer Graphics Forum}, title = {{
Interactive Modeling of Cellular Structures on Surfaces with Application to Additive Manufacturing}},
author = {
Stadlbauer, Pascal
and
Mlakar, Daniel
and
Seidel, Hans-Peter
and
Steinberger, Markus
and
Zayer, Rhaleb
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13929}
}
                
@article{
10.1111:cgf.13930,
journal = {Computer Graphics Forum}, title = {{
Illumination-Guided Furniture Layout Optimization}},
author = {
Vitsas, Nick
and
Papaioannou, Georgios
and
Gkaravelis, Anastasios
and
Vasilakis, Andreas-Alexandros
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13930}
}
                
@article{
10.1111:cgf.13931,
journal = {Computer Graphics Forum}, title = {{
Polygon Laplacian Made Simple}},
author = {
Bunge, Astrid
and
Herholz, Philipp
and
Kazhdan, Misha
and
Botsch, Mario
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13931}
}
                
@article{
10.1111:cgf.13932,
journal = {Computer Graphics Forum}, title = {{
Spectral Mesh Simplification}},
author = {
Lescoat, Thibault
and
Liu, Hsueh-Ti Derek
and
Thiery, Jean-Marc
and
Jacobson, Alec
and
Boubekeur, Tamy
and
Ovsjanikov, Maks
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13932}
}
                
@article{
10.1111:cgf.13933,
journal = {Computer Graphics Forum}, title = {{
Fast and Robust QEF Minimization using Probabilistic Quadrics}},
author = {
Trettner, Philip
and
Kobbelt, Leif
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13933}
}
                
@article{
10.1111:cgf.13934,
journal = {Computer Graphics Forum}, title = {{
Subdivision-Specialized Linear Algebra Kernels for Static and Dynamic Mesh Connectivity on the GPU}},
author = {
Mlakar, Daniel
and
Winter, Martin
and
Stadlbauer, Pascal
and
Seidel, Hans-Peter
and
Steinberger, Markus
and
Zayer, Rhaleb
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13934}
}
                
@article{
10.1111:cgf.13935,
journal = {Computer Graphics Forum}, title = {{
Stratified Markov Chain Monte Carlo Light Transport}},
author = {
Gruson, Adrien
and
West, Rex
and
Hachisuka, Toshiya
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13935}
}
                
@article{
10.1111:cgf.13936,
journal = {Computer Graphics Forum}, title = {{
An Efficient Transport Estimator for Complex Layered Materials}},
author = {
Gamboa, Luis E.
and
Gruson, Adrien
and
Nowrouzezahrai, Derek
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13936}
}
                
@article{
10.1111:cgf.13937,
journal = {Computer Graphics Forum}, title = {{
Spectral Mollification for Bidirectional Fluorescence}},
author = {
Jung, Alisa
and
Hanika, Johannes
and
Dachsbacher, Carsten
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13937}
}
                
@article{
10.1111:cgf.13938,
journal = {Computer Graphics Forum}, title = {{
Fast and Robust Stochastic Structural Optimization}},
author = {
Cui, Qiaodong
and
Langlois, Timothy
and
Sen, Pradeep
and
Kim, Theodore
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13938}
}
                
@article{
10.1111:cgf.13939,
journal = {Computer Graphics Forum}, title = {{
Computational Design and Optimization of Non-Circular Gears}},
author = {
Xu, Hao
and
Fu, Tianwen
and
Song, Peng
and
Zhou, Mingjun
and
Fu, Chi-Wing
and
Mitra, Niloy J.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13939}
}
                
@article{
10.1111:cgf.13940,
journal = {Computer Graphics Forum}, title = {{
Designing Robotically-Constructed Metal Frame Structures}},
author = {
Ma, Zhao
and
Walzer, Alexander
and
Schumacher, Christian
and
Rust, Romana
and
Gramazio, Fabio
and
Kohler, Matthias
and
Bächer, Moritz
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13940}
}
                
@article{
10.1111:cgf.13941,
journal = {Computer Graphics Forum}, title = {{
Optimizing Object Decomposition to Reduce Visual Artifacts in 3D Printing}},
author = {
Filoscia, Irene
and
Alderighi, Thomas
and
Giorgi, Daniela
and
Malomo, Luigi
and
Callieri, Marco
and
Cignoni, Paolo
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13941}
}
                
@article{
10.1111:cgf.13942,
journal = {Computer Graphics Forum}, title = {{
Prefilters for Sharp Image Display}},
author = {
Rocha, Luís Cláudio Gouveia
and
Oliveira, Manuel M.
and
Gastal, Eduardo S. L.
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13942}
}
                
@article{
10.1111:cgf.13943,
journal = {Computer Graphics Forum}, title = {{
RGB2AO: Ambient Occlusion Generation from RGB Images}},
author = {
Inoue, Naoto
and
Ito, Daichi
and
Hold-Geoffroy, Yannick
and
Mai, Long
and
Price, Brian
and
Yamasaki, Toshihiko
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13943}
}
                
@article{
10.1111:cgf.13944,
journal = {Computer Graphics Forum}, title = {{
Single Sensor Compressive Light Field Video Camera}},
author = {
Hajisharif, Saghi
and
Miandji, Ehsan
and
Guillemot, Christine
and
Unger, Jonas
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13944}
}
                
@article{
10.1111:cgf.13945,
journal = {Computer Graphics Forum}, title = {{
Accurate Real-time 3D Gaze Tracking Using a Lightweight Eyeball Calibration}},
author = {
Wen, Quan
and
Bradley, Derek
and
Beeler, Thabo
and
Park, Seonwook
and
Hilliges, Otmar
and
Yong, Jun-Hai
and
Xu, Feng
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13945}
}
                
@article{
10.1111:cgf.13946,
journal = {Computer Graphics Forum}, title = {{
Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows}},
author = {
Alexanderson, Simon
and
Henter, Gustav Eje
and
Kucherenko, Taras
and
Beskow, Jonas
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13946}
}
                
@article{
10.1111:cgf.13947,
journal = {Computer Graphics Forum}, title = {{
Motion Retargetting based on Dilated Convolutions and Skeleton-specific Loss Functions}},
author = {
Kim, SangBin
and
Park, Inbum
and
Kwon, Seongsu
and
Han, JungHyun
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13947}
}
                
@article{
10.1111:cgf.13949,
journal = {Computer Graphics Forum}, title = {{
Real-time Anticipation of Occlusions for Automated Camera Control in Toric Space}},
author = {
Burg, Ludovic
and
Lino, Christophe
and
Christie, Marc
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13949}
}
                
@article{
10.1111:cgf.13948,
journal = {Computer Graphics Forum}, title = {{
Binary Ostensibly-Implicit Trees for Fast Collision Detection}},
author = {
Chitalu, Floyd M.
and
Dubach, Christophe
and
Komura, Taku
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13948}
}
                
@article{
10.1111:cgf.13950,
journal = {Computer Graphics Forum}, title = {{
Efficient Minimum Distance Computation for Solids of Revolution}},
author = {
Son, Sang-Hyun
and
Yoon, Seung-Hyun
and
Kim, Myung-Soo
and
Elber, Gershon
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13950}
}
                
@article{
10.1111:cgf.13951,
journal = {Computer Graphics Forum}, title = {{
Segment Tracing Using Local Lipschitz Bounds}},
author = {
Galin, Eric
and
Guérin, Eric
and
Paris, Axel
and
Peytavie, Adrien
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13951}
}
                
@article{
10.1111:cgf.13952,
journal = {Computer Graphics Forum}, title = {{
Robust Shape Collection Matching and Correspondence from Shape Differences}},
author = {
Cohen, Aharon
and
Ben-Chen, Mirela
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13952}
}
                
@article{
10.1111:cgf.13953,
journal = {Computer Graphics Forum}, title = {{
Displacement-Correlated XFEM for Simulating Brittle Fracture}},
author = {
Chitalu, Floyd M.
and
Miao, Qinghai
and
Subr, Kartic
and
Komura, Taku
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13953}
}
                
@article{
10.1111:cgf.13954,
journal = {Computer Graphics Forum}, title = {{
Interactive Meso-scale Simulation of Skyscapes}},
author = {
Vimont, Ulysse
and
Gain, James
and
Lastic, Maud
and
Cordonnier, Guillaume
and
Abiodun, Babatunde
and
Cani, Marie-Paule
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13954}
}
                
@article{
10.1111:cgf.13955,
journal = {Computer Graphics Forum}, title = {{
Simulation of Dendritic Painting}},
author = {
Canabal, José A.
and
Otaduy, Miguel A.
and
Kim, Byungmoon
and
Echevarria, Jose
}, year = {
2020},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.13955}
}

Browse

Recent Submissions

Now showing 1 - 50 of 50
  • Item
    EUROGRAPHICS 2020: CGF 39-2 Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Assarsson, Ulf; Panozzo, Daniele; Panozzo, Daniele and Assarsson, Ulf
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  • Item
    Asynchronous Eulerian Liquid Simulation
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Koike, Tatsuya; Morishima, Shigeo; Ando, Ryoichi; Panozzo, Daniele and Assarsson, Ulf
    We present a novel method for simulating liquid with asynchronous time steps on Eulerian grids. Previous approaches focus on Smoothed Particle Hydrodynamics (SPH), Material Point Method (MPM) or tetrahedral Finite Element Method (FEM) but the method for simulating liquid purely on Eulerian grids have not yet been investigated. We address several challenges specifically arising from the Eulerian asynchronous time integrator such as regional pressure solve, asynchronous advection, interpolation, regional volume preservation, and dedicated segregation of the simulation domain according to the liquid velocity. We demonstrate our method on top of staggered grids combined with the level set method and the semi-Lagrangian scheme. We run several examples and show that our method considerably outperforms the global adaptive time step method with respect to the computational runtime on scenes where a large variance of velocity is present.
  • Item
    Local Bases for Model-reduced Smoke Simulations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Mercier, Olivier; Nowrouzezahrai, Derek; Panozzo, Daniele and Assarsson, Ulf
    We present a flexible model reduction method for simulating incompressible fluids.We derive a novel vector field basis composed of localized basis flows which have simple analytic forms and can be tiled on regular lattices, avoiding the use of complicated data structures or neighborhood queries. Local basis flow interactions can be precomputed and reused to simulate fluid dynamics on any simulation domain without additional overhead. We introduce heuristic simulation dynamics tailored to our basis and derived from a projection of the Navier-Stokes equations to produce physically plausible motion, exposing intuitive parameters to control energy distribution across scales. Our basis can adapt to curved simulation boundaries, can be coupled with dynamic obstacles, and offers simple adjustable trade-offs between speed and visual resolution.
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    Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lai, Junyu; Chen, Yangang; Gu, Yu; Batty, Christopher; Wan, Justin W. L.; Panozzo, Daniele and Assarsson, Ulf
    In this paper, we propose and evaluate fast, scalable approaches for solving the linear complementarity problems (LCP) arising from the fluid pressure equations with separating solid boundary conditions. Specifically, we present a policy iteration method, a penalty method, and a modified multigrid method, and demonstrate that each is able to properly handle the desired boundary conditions. Moreover, we compare our proposed methods against existing approaches and show that our solvers are more efficient and exhibit better scaling behavior; that is, the number of iterations required for convergence is essentially independent of grid resolution, and thus they are faster at larger grid resolutions. For example, on a 256 grid our multigrid method was 30 times faster than the prior multigrid method in the literature.
  • Item
    Persistence Analysis of Multi-scale Planar Structure Graph in Point Clouds
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lejemble, Thibault; Mura, Claudio; Barthe, Loïc; Mellado, Nicolas; Panozzo, Daniele and Assarsson, Ulf
    Modern acquisition techniques generate detailed point clouds that sample complex geometries. For instance, we are able to produce millimeter-scale acquisition of whole buildings. Processing and exploring geometrical information within such point clouds requires scalability, robustness to acquisition defects and the ability to model shapes at different scales. In this work, we propose a new representation that enriches point clouds with a multi-scale planar structure graph. We define the graph nodes as regions computed with planar segmentations at increasing scales and the graph edges connect regions that are similar across scales. Connected components of the graph define the planar structures present in the point cloud within a scale interval. For instance, with this information, any point is associated to one or several planar structures existing at different scales. We then use topological data analysis to filter the graph and provide the most prominent planar structures. Our representation naturally encodes a large range of information. We show how to efficiently extract geometrical details (e.g. tiles of a roof), arrangements of simple shapes (e.g. steps and mean ramp of a staircase), and large-scale planar proxies (e.g. walls of a building) and present several interactive tools to visualize, select and reconstruct planar primitives directly from raw point clouds. The effectiveness of our approach is demonstrated by an extensive evaluation on a variety of input data, as well as by comparing against state-of-the-art techniques and by showing applications to polygonal mesh reconstruction.
  • Item
    Progressive Real-Time Rendering of One Billion Points Without Hierarchical Acceleration Structures
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Schütz, Markus; Mandlburger, Gottfried; Otepka, Johannes; Wimmer, Michael; Panozzo, Daniele and Assarsson, Ulf
    Research in rendering large point clouds traditionally focused on the generation and use of hierarchical acceleration structures that allow systems to load and render the smallest fraction of the data with the largest impact on the output. The generation of these structures is slow and time consuming, however, and therefore ill-suited for tasks such as quickly looking at scan data stored in widely used unstructured file formats, or to immediately display the results of point-cloud processing tasks. We propose a progressive method that is capable of rendering any point cloud that fits in GPU memory in real time, without the need to generate hierarchical acceleration structures in advance. Our method supports data sets with a large amount of attributes per point, achieves a load performance of up to 100 million points per second, displays already loaded data in real time while remaining data is still being loaded, and is capable of rendering up to one billion points using an on-the-fly generated shuffled vertex buffer as its data structure, instead of slow-to-generate hierarchical structures. Shuffling is done during loading in order to allow efficiently filling holes with random subsets, which leads to a higher quality convergence behavior.
  • Item
    SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Santesteban, Igor; Garces, Elena; Otaduy, Miguel A.; Casas, Dan; Panozzo, Daniele and Assarsson, Ulf
    We present SoftSMPL, a learning-based method to model realistic soft-tissue dynamics as a function of body shape and motion. Datasets to learn such task are scarce and expensive to generate, which makes training models prone to overfitting. At the core of our method there are three key contributions that enable us to model highly realistic dynamics and better generalization capabilities than state-of-the-art methods, while training on the same data. First, a novel motion descriptor that disentangles the standard pose representation by removing subject-specific features; second, a neural-network-based recurrent regressor that generalizes to unseen shapes and motions; and third, a highly efficient nonlinear deformation subspace capable of representing soft-tissue deformations of arbitrary shapes. We demonstrate qualitative and quantitative improvements over existing methods and, additionally, we show the robustness of our method on a variety of motion capture databases.
  • Item
    Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Romero, Cristian; Otaduy, Miguel A.; Casas, Dan; Pérez, Jesús; Panozzo, Daniele and Assarsson, Ulf
    Data-driven models of human avatars have shown very accurate representations of static poses with soft-tissue deformations. However they are not yet capable of precisely representing very nonlinear deformations and highly dynamic effects. Nonlinear skin mechanics are essential for a realistic depiction of animated avatars interacting with the environment, but controlling physics-only solutions often results in a very complex parameterization task. In this work, we propose a hybrid model in which the soft-tissue deformation of animated avatars is built as a combination of a data-driven statistical model, which kinematically drives the animation, an FEM mechanical simulation. Our key contribution is the definition of deformation mechanics in a reference pose space by inverse skinning of the statistical model. This way, we retain as much as possible of the accurate static data-driven deformation and use a custom anisotropic nonlinear material to accurately represent skin dynamics. Model parameters including the heterogeneous distribution of skin thickness and material properties are automatically optimized from 4D captures of humans showing soft-tissue deformations.
  • Item
    A Practical Method for Animating Anisotropic Elastoplastic Materials
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Schreck, Camille; Wojtan, Chris; Panozzo, Daniele and Assarsson, Ulf
    This paper introduces a simple method for simulating highly anisotropic elastoplastic material behaviors like the dissolution of fibrous phenomena (splintering wood, shredding bales of hay) and materials composed of large numbers of irregularly-shaped bodies (piles of twigs, pencils, or cards). We introduce a simple transformation of the anisotropic problem into an equivalent isotropic one, and we solve this new ''fictitious'' isotropic problem using an existing simulator based on the material point method. Our approach results in minimal changes to existing simulators, and it allows us to re-use popular isotropic plasticity models like the Drucker-Prager yield criterion instead of inventing new anisotropic plasticity models for every phenomenon we wish to simulate.
  • Item
    Mixing Yarns and Triangles in Cloth Simulation
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Casafranca, Juan J.; Cirio, Gabriel; Rodríguez, Alejandro; Miguel, Eder; Otaduy, Miguel A.; Panozzo, Daniele and Assarsson, Ulf
    This paper presents a method to combine triangle and yarn models in cloth simulation, and hence leverage their best features. The majority of a garment uses a triangle-based model, which reduces the overall computational and memory cost. Key areas of the garment use a yarn-based model, which elicits rich effects such as structural nonlinearity and plasticity. To combine both models in a seamless and robust manner, we solve two major technical challenges. We propose an enriched kinematic representation that augments triangle-based deformations with yarn-level details. Naïve enrichment suffers from kinematic redundancy, but we devise an optimal kinematic filter that allows a smooth transition between triangle and yarn models. We also introduce a preconditioner that resolves the poor conditioning produced by the extremely different inertia of triangle and yarn nodes. This preconditioner deals effectively with rank deficiency introduced by the kinematic filter. We demonstrate that mixed yarns and triangles succeed to efficiently capture rich effects in garment fit and drape.
  • Item
    Interactively Modifying Compressed Sparse Voxel Representations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Careil, Victor; Billeter, Markus; Eisemann, Elmar; Panozzo, Daniele and Assarsson, Ulf
    Voxels are a popular choice to encode complex geometry. Their regularity makes updates easy and enables random retrieval of values. The main limitation lies in the poor scaling with respect to resolution. Sparse voxel DAGs (Directed Acyclic Graphs) overcome this hurdle and offer high-resolution representations for real-time rendering but only handle static data. We introduce a novel data structure to enable interactive modifications of such compressed voxel geometry without requiring de- and recompression. Besides binary data to encode geometry, it also supports compressed attributes (e.g., color). We illustrate the usefulness of our representation via an interactive large-scale voxel editor (supporting carving, filling, copying, and painting).
  • Item
    UV-free Texturing using Sparse Voxel DAGs
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Dolonius, Dan; Sintorn, Erik; Assarsson, Ulf; Panozzo, Daniele and Assarsson, Ulf
    An application may have to load an unknown 3D model and, for enhanced realistic rendering, precompute values over the surface domain, such as light maps, ambient occlusion, or other global-illumination parameters. High-quality uv-unwrapping has several problems, such as seams, distortions, and wasted texture space. Additionally, procedurally generated scene content, perhaps on the fly, can make manual uv unwrapping impossible. Even when artist manipulation is feasible, good uv layouts can require expertise and be highly labor intensive. This paper investigates how to use Sparse Voxel DAGs (or DAGs for short) as one alternative to avoid uv mapping. The result is an algorithm enabling high compression ratios of both voxel structure and colors, which can be important for a baked scene to fit in GPU memory. Specifically, we enable practical usage for an automatic system by targeting efficient real-time mipmap filtering using compressed textures and adding support for individual mesh voxelizations and resolutions in the same DAG. Furthermore, the latter increases the texture-compression ratios by up to 32% compared to using one global voxelization, DAG compression by 10-15% compared to using a DAG per mesh, and reduces color-bleeding problems for large mipmap filter sizes. The voxel-filtering is more costly than standard hardware 2D-texture filtering. However, for full HD with deferred shading, it is optimized down to 2:5 +/- 0:5 ms for a custom multisampling filtering (e.g., targeted for minification of low-frequency textures) and 5 +/- 2 ms for quad-linear mipmap filtering (e.g., for high-frequency textures). Multiple textures sharing voxelization can amortize the majority of this cost. Hence, these numbers involve 1-3 textures per pixel (Fig. 1c).
  • Item
    Spherical Gaussian Light-field Textures for Fast Precomputed Global Illumination
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Currius, Roc Ramon; Dolonius, Dan; Assarsson, Ulf; Sintorn, Erik; Panozzo, Daniele and Assarsson, Ulf
    We describe a method to use Spherical Gaussians with free directions and arbitrary sharpness and amplitude to approximate the precomputed local light field for any point on a surface in a scene. This allows for a high-quality reconstruction of these light fields in a manner that can be used to render the surfaces with precomputed global illumination in real-time with very low cost both in memory and performance. We also extend this concept to represent the illumination-weighted environment visibility, allowing for high-quality reflections of the distant environment with both surface-material properties and visibility taken into account. We treat obtaining the Spherical Gaussians as an optimization problem for which we train a Convolutional Neural Network to produce appropriate values for each of the Spherical Gaussians' parameters. We define this CNN in such a way that the produced parameters can be interpolated between adjacent local light fields while keeping the illumination in the intermediate points coherent
  • Item
    Neural Temporal Adaptive Sampling and Denoising
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hasselgren, Jon; Munkberg, Jacob; Salvi, Marco; Patney, Anjul; Lefohn, Aaron; Panozzo, Daniele and Assarsson, Ulf
    Despite recent advances in Monte Carlo path tracing at interactive rates, denoised image sequences generated with few samples per-pixel often yield temporally unstable results and loss of high-frequency details. We present a novel adaptive rendering method that increases temporal stability and image fidelity of low sample count path tracing by distributing samples via spatio-temporal joint optimization of sampling and denoising. Adding temporal optimization to the sample predictor enables it to learn spatio-temporal sampling strategies such as placing more samples in disoccluded regions, tracking specular highlights, etc; adding temporal feedback to the denoiser boosts the effective input sample count and increases temporal stability. The temporal approach also allows us to remove the initial uniform sampling step typically present in adaptive sampling algorithms. The sample predictor and denoiser are deep neural networks that we co-train end-to-end over multiple consecutive frames. Our approach is scalable, allowing trade-off between quality and performance, and runs at near real-time rates while achieving significantly better image quality and temporal stability than previous methods.
  • Item
    DeepBRDF: A Deep Representation for Manipulating Measured BRDF
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hu, Bingyang; Guo, Jie; Chen, Yanjun; Li, Mengtian; Guo, Yanwen; Panozzo, Daniele and Assarsson, Ulf
    Effective compression of densely sampled BRDF measurements is critical for many graphical or vision applications. In this paper, we present DeepBRDF, a deep-learning-based representation that can significantly reduce the dimensionality of measured BRDFs while enjoying high quality of recovery. We consider each measured BRDF as a sequence of image slices and design a deep autoencoder with a masked L2 loss to discover a nonlinear low-dimensional latent space of the high-dimensional input data. Thorough experiments verify that the proposed method clearly outperforms PCA-based strategies in BRDF data compression and is more robust. We demonstrate the effectiveness of DeepBRDF with two applications. For BRDF editing, we can easily create a new BRDF by navigating on the low-dimensional manifold of DeepBRDF, guaranteeing smooth transitions and high physical plausibility. For BRDF recovery, we design another deep neural network to automatically generate the full BRDF data from a single input image. Aided by our DeepBRDF learned from real-world materials, a wide range of reflectance behaviors can be recovered with high accuracy.
  • Item
    Unified Neural Encoding of BTFs
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Rainer, Gilles; Ghosh, Abhijeet; Jakob, Wenzel; Weyrich, Tim; Panozzo, Daniele and Assarsson, Ulf
    Realistic rendering using discrete reflectance measurements is challenging, because arbitrary directions on the light and view hemispheres are queried at render time, incurring large memory requirements and the need for interpolation. This explains the desire for compact and continuously parametrized models akin to analytic BRDFs; however, fitting BRDF parameters to complex data such as BTF texels can prove challenging, as models tend to describe restricted function spaces that cannot encompass real-world behavior. Recent advances in this area have increasingly relied on neural representations that are trained to reproduce acquired reflectance data. The associated training process is extremely costly and must typically be repeated for each material. Inspired by autoencoders, we propose a unified network architecture that is trained on a variety of materials, and which projects reflectance measurements to a shared latent parameter space. Similarly to SVBRDF fitting, real-world materials are represented by parameter maps, and the decoder network is analog to the analytic BRDF expression (also parametrized on light and view directions for practical rendering application). With this approach, encoding and decoding materials becomes a simple matter of evaluating the network. We train and validate on BTF datasets of the University of Bonn, but there are no prerequisites on either the number of angular reflectance samples, or the sample positions. Additionally, we show that the latent space is well-behaved and can be sampled from, for applications such as mipmapping and texture synthesis.
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    Combinatorial Construction of Seamless Parameter Domains
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Zhou, Jiaran; Tu, Changhe; Zorin, Denis; Campen, Marcel; Panozzo, Daniele and Assarsson, Ulf
    The problem of seamless parametrization of surfaces is of interest in the context of structured quadrilateral mesh generation and spline-based surface approximation. It has been tackled by a variety of approaches, commonly relying on continuous numerical optimization to ultimately obtain suitable parameter domains. We present a general combinatorial seamless parameter domain construction, free from the potential numerical issues inherent to continuous optimization techniques in practice. The domains are constructed as abstract polygonal complexes which can be embedded in a discrete planar grid space, as unions of unit squares. We ensure that the domain structure matches any prescribed parametrization singularities (cones) and satisfies seamlessness conditions. Surfaces of arbitrary genus are supported. Once a domain suitable for a given surface is constructed, a seamless and locally injective parametrization over this domain can be obtained using existing planar disk mapping techniques, making recourse to Tutte's classical embedding theorem.
  • Item
    Greedy Cut Construction for Parameterizations
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Zhu, Tianyu; Ye, Chunyang; Chai, Shuangming; Fu, Xiao-Ming; Panozzo, Daniele and Assarsson, Ulf
    We present a novel method to construct short cuts for parameterizations with low isometric distortion. The algorithm contains two steps: (i) detect feature points, where the distortion is usually concentrated; and (ii) construct a cut by connecting the detected feature points. Central to each step is a greedy method. After generating a redundant feature point set, a greedy filtering process is performed to identify the feature points required for low isometric distortion parameterizations. This filtering process discards the feature points that are useless for distortion reduction while still enabling us to obtain low isometric distortion. Next, we formulate the process of connecting the detected feature points as a Steiner tree problem. To find an approximate solution, we first successively and greedily produce a collection of auxiliary points. Then, a cut is constructed by connecting the feature points and auxiliary points. In the 26,299 test cases in which an exact solution to the Steiner tree problem is available, the length of the cut obtained by our method is on average 0.17% longer than optimal. Compared to state-of-the-art cut construction methods, our method is one order of magnitude faster and generates shorter cuts while achieving similar isometric distortion.
  • Item
    Locally Supported Tangential Vector, n-Vector, and Tensor Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Nasikun, Ahmad; Brandt, Christopher; Hildebrandt, Klaus; Panozzo, Daniele and Assarsson, Ulf
    We introduce a construction of subspaces of the spaces of tangential vector, n-vector, and tensor fields on surfaces. The resulting subspaces can be used as the basis of fast approximation algorithms for design and processing problems that involve tangential fields. Important features of our construction are that it is based on a general principle, from which constructions for different types of tangential fields can be derived, and that it is scalable, making it possible to efficiently compute and store large subspace bases for large meshes. Moreover, the construction is adaptive, which allows for controlling the distribution of the degrees of freedom of the subspaces over the surface. We evaluate our construction in several experiments addressing approximation quality, scalability, adaptivity, computation times and memory requirements. Our design choices are justified by comparing our construction to possible alternatives. Finally, we discuss examples of how subspace methods can be used to build interactive tools for tangential field design and processing tasks.
  • Item
    Expression Packing: As-Few-As-Possible Training Expressions for Blendshape Transfer
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Carrigan, Emma; Zell, Eduard; Guiard, Cedric; McDonnell, Rachel; Panozzo, Daniele and Assarsson, Ulf
    To simplify and accelerate the creation of blendshape rigs, using a template rig is a common procedure, especially during the creation of digital doubles. Blendshape transfer methods facilitate copy and paste functionality of the blendshapes from the template model to the digital double. However, for adequate personalization, such methods require a set of scanned training expressions of the original actor. So far, the semantics of the facial expressions to scan have been defined manually. In contrast, we formulate the semantics of the facial expressions as an integer optimization of the blendshape weights. By combining different blendshapes of the template model, our method creates facial expressions that serve as semantic references during scanning. Our method guarantees to compute as-few-as-possible training expressions with minimal overlap of activated blendshapes. If the number of training expressions is limited, blendshapes are selected based on their power to personalize the resulting blendshapes compared to generic blendshape transfer methods.
  • Item
    Facial Expression Synthesis using a Global-Local Multilinear Framework
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wang, Mengjiao; Bradley, Derek; Zafeiriou, Stefanos; Beeler, Thabo; Panozzo, Daniele and Assarsson, Ulf
    We present a practical method to synthesize plausible 3D facial expressions for a particular target subject. The ability to synthesize an entire facial rig from a single neutral expression has a large range of applications both in computer graphics and computer vision, ranging from the efficient and cost-effective creation of CG characters to scalable data generation for machine learning purposes. Unlike previous methods based on multilinear models, the proposed approach is capable to extrapolate well outside the sample pool, which allows it to plausibly predict the identity of the target subject and create artifact free expression shapes while requiring only a small input dataset. We introduce global-local multilinear models that leverage the strengths of expression-specific and identity-specific local models combined with coarse motion estimations from a global model. Experimental results show that we achieve high-quality, plausible facial expression synthesis results for an individual that outperform existing methods both quantitatively and qualitatively.
  • Item
    Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Fratarcangeli, Marco; Bradley, Derek; Gruber, Aurel; Zoss, Gaspard; Beeler, Thabo; Panozzo, Daniele and Assarsson, Ulf
    Many problems in computer graphics and vision can be formulated as a nonlinear least squares optimization problem, for which numerous off-the-shelf solvers are readily available. Depending on the structure of the problem, however, existing solvers may be more or less suitable, and in some cases the solution comes at the cost of lengthy convergence times. One such case is semi-sparse optimization problems, emerging for example in localized facial performance reconstruction, where the nonlinear least squares problem can be composed of hundreds of thousands of cost functions, each one involving many of the optimization parameters. While such problems can be solved with existing solvers, the computation time can severely hinder the applicability of these methods. We introduce a novel iterative solver for nonlinear least squares optimization of large-scale semi-sparse problems. We use the nonlinear Levenberg-Marquardt method to locally linearize the problem in parallel, based on its firstorder approximation. Then, we decompose the linear problem in small blocks, using the local Schur complement, leading to a more compact linear system without loss of information. The resulting system is dense but its size is small enough to be solved using a parallel direct method in a short amount of time. The main benefit we get by using such an approach is that the overall optimization process is entirely parallel and scalable, making it suitable to be mapped onto graphics hardware (GPU). By using our minimizer, results are obtained up to one order of magnitude faster than other existing solvers, without sacrificing the generality and the accuracy of the model. We provide a detailed analysis of our approach and validate our results with the application of performance-based facial capture using a recently-proposed anatomical local face deformation model.
  • Item
    Invertible Paradoxic Loop Structures for Transformable Design
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Li, Zijia; Nawratil, Georg; Rist, Florian; Hensel, Michael; Panozzo, Daniele and Assarsson, Ulf
    We present an interactive tool compatible with existing software (Rhino/Grasshopper) to design ring structures with a paradoxic mobility, which are self-collision-free over the complete motion cycle. Our computational approach allows non-expert users to create these invertible paradoxic loops with six rotational joints by providing several interactions that facilitate design exploration. In a first step, a rational cubic motion is shaped either by means of a four pose interpolation procedure or a motion evolution algorithm. By using the representation of spatial displacements in terms of dual-quaternions, the associated motion polynomial of the resulting motion can be factored in several ways, each corresponding to a composition of three rotations. By combining two suitable factorizations, an arrangement of six rotary axes is achieved, which possesses a 1-parametric mobility. In the next step, these axes are connected by links in a way that the resulting linkage is collision-free over the complete motion cycle. Based on an algorithmic solution for this problem, collision-free design spaces of the individual links are generated in a post-processing step. The functionality of the developed design tool is demonstrated in the context of an architectural and artistic application studied in a master-level studio course. Two results of the performed design experiments were fabricated by the use of computer-controlled machines to achieve the necessary accuracy ensuring the mobility of the models.
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    Interactive Modeling of Cellular Structures on Surfaces with Application to Additive Manufacturing
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Stadlbauer, Pascal; Mlakar, Daniel; Seidel, Hans-Peter; Steinberger, Markus; Zayer, Rhaleb; Panozzo, Daniele and Assarsson, Ulf
    The rich and evocative patterns of natural tessellations endow them with an unmistakable artistic appeal and structural properties which are echoed across design, production, and manufacturing. Unfortunately, interactive control of such patterns-as modeled by Voronoi diagrams, is limited to the simple two dimensional case and does not extend well to freeform surfaces. We present an approach for direct modeling and editing of such cellular structures on surface meshes. The overall modeling experience is driven by a set of editing primitives which are efficiently implemented on graphics hardware. We feature a novel application for 3D printing on modern support-free additive manufacturing platforms. Our method decomposes the input surface into a cellular skeletal structure which hosts a set of overlay shells. In this way, material saving can be channeled to the shells while structural stability is channeled to the skeleton. To accommodate the available printer build volume, the cellular structure can be further split into moderately sized parts. Together with shells, they can be conveniently packed to save on production time. The assembly of the printed parts is streamlined by a part numbering scheme which respects the geometric layout of the input model.
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    Illumination-Guided Furniture Layout Optimization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Vitsas, Nick; Papaioannou, Georgios; Gkaravelis, Anastasios; Vasilakis, Andreas-Alexandros; Panozzo, Daniele and Assarsson, Ulf
    Lighting plays a very important role in interior design. However, in the specific problem of furniture layout recommendation, illumination has been either neglected or addressed with empirical or very simplified solutions. The effectiveness of a particular layout in its expected task performance can be greatly affected by daylighting and artificial illumination in a non-trivial manner. In this paper, we introduce a robust method for furniture layout optimization guided by illumination constraints. The method takes into account all dominant light sources, such as sun light, skylighting and fixtures, while also being able to handle movable light emitters. For this task, the method introduces multiple generic illumination constraints and physically-based light transport estimators, operating alongside typical geometric design guidelines, in a unified manner. We demonstrate how to produce furniture arrangements that comply with important safety, comfort and efficiency illumination criteria, such as glare suppression, under complex light-environment interactions, which are very hard to handle using empirical or simplified models.
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    Polygon Laplacian Made Simple
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Bunge, Astrid; Herholz, Philipp; Kazhdan, Misha; Botsch, Mario; Panozzo, Daniele and Assarsson, Ulf
    The discrete Laplace-Beltrami operator for surface meshes is a fundamental building block for many (if not most) geometry processing algorithms. While Laplacians on triangle meshes have been researched intensively, yielding the cotangent discretization as the de-facto standard, the case of general polygon meshes has received much less attention. We present a discretization of the Laplace operator which is consistent with its expression as the composition of divergence and gradient operators, and is applicable to general polygon meshes, including meshes with non-convex, and even non-planar, faces. By virtually inserting a carefully placed point we implicitly refine each polygon into a triangle fan, but then hide the refinement within the matrix assembly. The resulting operator generalizes the cotangent Laplacian, inherits its advantages, and is empirically shown to be on par or even better than the recent polygon Laplacian of Alexa and Wardetzky [AW11] - while being simpler to compute.
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    Spectral Mesh Simplification
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Lescoat, Thibault; Liu, Hsueh-Ti Derek; Thiery, Jean-Marc; Jacobson, Alec; Boubekeur, Tamy; Ovsjanikov, Maks; Panozzo, Daniele and Assarsson, Ulf
    The spectrum of the Laplace-Beltrami operator is instrumental for a number of geometric modeling applications, from processing to analysis. Recently, multiple methods were developed to retrieve an approximation of a shape that preserves its eigenvectors as much as possible, but these techniques output a subset of input points with no connectivity, which limits their potential applications. Furthermore, the obtained Laplacian results from an optimization procedure, implying its storage alongside the selected points. Focusing on keeping a mesh instead of an operator would allow to retrieve the latter using the standard cotangent formulation, enabling easier processing afterwards. Instead, we propose to simplify the input mesh using a spectrum-preserving mesh decimation scheme, so that the Laplacian computed on the simplified mesh is spectrally close to the one of the input mesh. We illustrate the benefit of our approach for quickly approximating spectral distances and functional maps on low resolution proxies of potentially high resolution input meshes.
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    Fast and Robust QEF Minimization using Probabilistic Quadrics
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Trettner, Philip; Kobbelt, Leif; Panozzo, Daniele and Assarsson, Ulf
    Error quadrics are a fundamental and powerful building block in many geometry processing algorithms. However, finding the minimizer of a given quadric is in many cases not robust and requires a singular value decomposition or some ad-hoc regularization. While classical error quadrics measure the squared deviation from a set of ground truth planes or polygons, we treat the input data as genuinely uncertain information and embed error quadrics in a probabilistic setting (''probabilistic quadrics'') where the optimal point minimizes the expected squared error. We derive closed form solutions for the popular plane and triangle quadrics subject to (spatially varying, anisotropic) Gaussian noise. Probabilistic quadrics can be minimized robustly by solving a simple linear system-50x faster than SVD. We show that probabilistic quadrics have superior properties in tasks like decimation and isosurface extraction since they favor more uniform triangulations and are more tolerant to noise while still maintaining feature sensitivity. A broad spectrum of applications can directly benefit from our new quadrics as a drop-in replacement which we demonstrate with mesh smoothing via filtered quadrics and non-linear subdivision surfaces.
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    Subdivision-Specialized Linear Algebra Kernels for Static and Dynamic Mesh Connectivity on the GPU
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Mlakar, Daniel; Winter, Martin; Stadlbauer, Pascal; Seidel, Hans-Peter; Steinberger, Markus; Zayer, Rhaleb; Panozzo, Daniele and Assarsson, Ulf
    Subdivision surfaces have become an invaluable asset in production environments. While progress over the last years has allowed the use of graphics hardware to meet performance demands during animation and rendering, high-performance is limited to immutable mesh connectivity scenarios. Motivated by recent progress in mesh data structures, we show how the complete Catmull-Clark subdivision scheme can be abstracted in the language of linear algebra. While this high-level formulation allows for a fully parallel implementation with significant performance gains, the underlying algebraic operations require further specialization for modern parallel hardware. Integrating domain knowledge about the mesh matrix data structure, we replace costly general linear algebra operations like matrix-matrix multiplication by specialized kernels. By further considering innate properties of Catmull-Clark subdivision, like the quad-only structure after refinement, we achieve an additional order of magnitude in performance and significantly reduce memory footprints. Our approach can be adapted seamlessly for different use cases, such as regular subdivision of dynamic meshes, fast evaluation for immutable topology and feature-adaptive subdivision for efficient rendering of animated models. In this way, patchwork solutions are avoided in favor of a streamlined solution with consistent performance gains throughout the production pipeline. The versatility of the sparse matrix linear algebra abstraction underlying our work is further demonstrated by extension to other schemes such as √3 and Loop subdivision.
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    Stratified Markov Chain Monte Carlo Light Transport
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Gruson, Adrien; West, Rex; Hachisuka, Toshiya; Panozzo, Daniele and Assarsson, Ulf
    Markov chain Monte Carlo (MCMC) sampling is a powerful approach to generate samples from an arbitrary distribution. The application to light transport simulation allows us to efficiently handle complex light transport such as highly occluded scenes. Since light transport paths in MCMC methods are sampled according to the path contributions over the sampling domain covering the whole image, bright pixels receive more samples than dark pixels to represent differences in the brightness. This variation in the number of samples per pixel is a fundamental property of MCMC methods. This property often leads to uneven convergence over the image, which is a notorious and fundamental issue of any MCMC method to date. We present a novel stratification method of MCMC light transport methods. Our stratification method, for the first time, breaks the fundamental limitation that the number of samples per pixel is uncontrollable. Our method guarantees that every pixel receives a specified number of samples by running a single Markov chain per pixel. We rely on the fact that different MCMC processes should converge to the same result when the sampling domain and the integrand are the same. We thus subdivide an image into multiple overlapping tiles associated with each pixel, run an independent MCMC process in each of them, and then align all of the tiles such that overlapping regions match. This can be formulated as an optimization problem similar to the reconstruction step for gradient-domain rendering. Further, our method can exploit the coherency of integrands among neighboring pixels via coherent Markov chains and replica exchange. Images rendered with our method exhibit much more predictable convergence compared to existing MCMC methods.
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    An Efficient Transport Estimator for Complex Layered Materials
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Gamboa, Luis E.; Gruson, Adrien; Nowrouzezahrai, Derek; Panozzo, Daniele and Assarsson, Ulf
    Layered materials capture subtle, realistic reflection behaviors that traditional single-layer models lack. Much of this is due to the complex subsurface light transport at the interfaces of - and in the media between - layers. Rendering with these materials can be costly, since we must simulate these transport effects at every evaluation of the underlying reflectance model. Rendering an image requires thousands of such evaluations, per pixel. Recent work treats this complexity by introducing significant approximations, requiring large precomputed datasets per material, or simplifying the light transport simulations within the materials. Even the most effective of these methods struggle with the complexity induced by high-frequency variation in reflectance parameters and micro-surface normal variation, as well as anisotropic volumetric scattering between the layer interfaces. We present a more efficient, unbiased estimator for light transport in such general, complex layered appearance models. By conducting an analysis of the types of transport paths that contribute most to the aggregate reflectance dynamics, we propose an effective and unbiased path sampling method that reduces variance in the reflectance evaluations. Our method additionally supports reflectance importance sampling, does not rely on any precomputation, and so integrates readily into existing renderers. We consistently outperform the state-of-the-art by ~2-6x in equal-quality (i.e., equal error) comparisons.
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    Spectral Mollification for Bidirectional Fluorescence
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Jung, Alisa; Hanika, Johannes; Dachsbacher, Carsten; Panozzo, Daniele and Assarsson, Ulf
    Fluorescent materials can shift energy between wavelengths, thereby creating bright and saturated colors both in natural and artificial materials. However, rendering fluorescence for continuous wavelengths or combined with wavelength dependent path configurations so far has only been feasible using spectral unidirectional methods. We present a regularization-based approach for supporting fluorescence in a spectral bidirectional path tracer. Our algorithm samples camera and light sub-paths with independent wavelengths, and when connecting them mollifies the BSDF at one of the connecting vertices such that it reradiates light across multiple wavelengths. We discuss arising issues such as color bias in early iterations, consistency of the method and MIS weights in the presence of spectral mollification. We demonstrate our method in scenes combining fluorescence and transport phenomena that are difficult to render with unidirectional or spectrally discrete methods.
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    Fast and Robust Stochastic Structural Optimization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Cui, Qiaodong; Langlois, Timothy; Sen, Pradeep; Kim, Theodore; Panozzo, Daniele and Assarsson, Ulf
    Stochastic structural analysis can assess whether a fabricated object will break under real-world conditions. While this approach is powerful, it is also quite slow, which has previously limited its use to coarse resolutions (e.g., 26x34x28). We show that this approach can be made asymptotically faster, which in practice reduces computation time by two orders of magnitude, and allows the use of previously-infeasible resolutions. We achieve this by showing that the probability gradient can be computed in linear time instead of quadratic, and by using a robust new scheme that stabilizes the inertia gradients used by the optimization. Additionally, we propose a constrained restart method that deals with local minima, and a sheathing approach that further reduces the weight of the shape. Together, these components enable the discovery of previously-inaccessible designs.
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    Computational Design and Optimization of Non-Circular Gears
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Xu, Hao; Fu, Tianwen; Song, Peng; Zhou, Mingjun; Fu, Chi-Wing; Mitra, Niloy J.; Panozzo, Daniele and Assarsson, Ulf
    We study a general form of gears known as non-circular gears that can transfer periodic motion with variable speed through their irregular shapes and eccentric rotation centers. To design functional non-circular gears is nontrivial, since the gear pair must have compatible shape to keep in contact during motion, so the driver gear can push the follower to rotate via a bounded torque that the motor can exert. To address the challenge, we model the geometry, kinematics, and dynamics of non-circular gears, formulate the design problem as a shape optimization, and identify necessary independent variables in the optimization search. Taking a pair of 2D shapes as inputs, our method optimizes them into gears by locating the rotation center on each shape, minimally modifying each shape to form the gear's boundary, and constructing appropriate teeth for gear meshing. Our optimized gears not only resemble the inputs but can also drive the motion with relatively small torque. We demonstrate our method's usability by generating a rich variety of non-circular gears from various inputs and 3D printing several of them.
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    Designing Robotically-Constructed Metal Frame Structures
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Ma, Zhao; Walzer, Alexander; Schumacher, Christian; Rust, Romana; Gramazio, Fabio; Kohler, Matthias; Bächer, Moritz; Panozzo, Daniele and Assarsson, Ulf
    We present a computational technique that aids with the design of structurally-sound metal frames, tailored for robotic fabrication using an existing process that integrate automated bar bending, welding, and cutting. Aligning frames with structurallyfavorable orientations, and decomposing models into fabricable units, we make the fabrication process scale-invariant, and frames globally align in an aesthetically-pleasing and structurally-informed manner. Relying on standard analysis of frames, we then co-optimize the shape and topology of bars at the local unit level. At this level, we minimize combinations of functional and aesthetic objectives under strict fabrication constraints that model the assembly of discrete sets of bent bars. We demonstrate the capabilities of our global-to-local approach on four robotically-constructed examples.
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    Optimizing Object Decomposition to Reduce Visual Artifacts in 3D Printing
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Filoscia, Irene; Alderighi, Thomas; Giorgi, Daniela; Malomo, Luigi; Callieri, Marco; Cignoni, Paolo; Panozzo, Daniele and Assarsson, Ulf
    We propose a method for the automatic segmentation of 3D objects into parts which can be individually 3D printed and then reassembled by preserving the visual quality of the final object. Our technique focuses on minimizing the surface affected by supports, decomposing the object into multiple parts whose printing orientation is automatically chosen. The segmentation reduces the visual impact on the fabricated model producing non-planar cuts that adapt to the object shape. This is performed by solving an optimization problem that balances the effects of supports and cuts, while trying to place both in occluded regions of the object surface. To assess the practical impact of the solution, we show a number of segmented, 3D printed and reassembled objects.
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    Prefilters for Sharp Image Display
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Rocha, Luís Cláudio Gouveia; Oliveira, Manuel M.; Gastal, Eduardo S. L.; Panozzo, Daniele and Assarsson, Ulf
    In this paper we use a simplified model of the human visual system to explain why humans tend do prefer ''sharpened'' digital images. From this model we then derive a family of image prefilters specifically adapted to viewing conditions and user preference, allowing for the trade-off between ringing and aliasing while maximizing image sharpness. We discuss how our filters can be applied in a variety of situations ranging from Monte Carlo rendering to image downscaling, and we show how they consistently give sharper results while having an efficient implementation and ease of use (there are no free parameters that require manual tuning). We demonstrate the effectiveness of our simple sharp prefilters through a user study that indicates a clear preference to our approach compared to the state-of-the-art.
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    RGB2AO: Ambient Occlusion Generation from RGB Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Inoue, Naoto; Ito, Daichi; Hold-Geoffroy, Yannick; Mai, Long; Price, Brian; Yamasaki, Toshihiko; Panozzo, Daniele and Assarsson, Ulf
    We present RGB2AO, a novel task to generate ambient occlusion (AO) from a single RGB image instead of screen space buffers such as depth and normal. RGB2AO produces a new image filter that creates a non-directional shading effect that darkens enclosed and sheltered areas. RGB2AO aims to enhance two 2D image editing applications: image composition and geometryaware contrast enhancement. We first collect a synthetic dataset consisting of pairs of RGB images and AO maps. Subsequently, we propose a model for RGB2AO by supervised learning of a convolutional neural network (CNN), considering 3D geometry of the input image. Experimental results quantitatively and qualitatively demonstrate the effectiveness of our model.
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    Single Sensor Compressive Light Field Video Camera
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Hajisharif, Saghi; Miandji, Ehsan; Guillemot, Christine; Unger, Jonas; Panozzo, Daniele and Assarsson, Ulf
    This paper presents a novel compressed sensing (CS) algorithm and camera design for light field video capture using a single sensor consumer camera module. Unlike microlens light field cameras which sacrifice spatial resolution to obtain angular information, our CS approach is designed for capturing light field videos with high angular, spatial, and temporal resolution. The compressive measurements required by CS are obtained using a random color-coded mask placed between the sensor and aperture planes. The convolution of the incoming light rays from different angles with the mask results in a single image on the sensor; hence, achieving a significant reduction on the required bandwidth for capturing light field videos. We propose to change the random pattern on the spectral mask between each consecutive frame in a video sequence and extracting spatioangular- spectral-temporal 6D patches. Our CS reconstruction algorithm for light field videos recovers each frame while taking into account the neighboring frames to achieve significantly higher reconstruction quality with reduced temporal incoherencies, as compared with previous methods. Moreover, a thorough analysis of various sensing models for compressive light field video acquisition is conducted to highlight the advantages of our method. The results show a clear advantage of our method for monochrome sensors, as well as sensors with color filter arrays.
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    Accurate Real-time 3D Gaze Tracking Using a Lightweight Eyeball Calibration
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Wen, Quan; Bradley, Derek; Beeler, Thabo; Park, Seonwook; Hilliges, Otmar; Yong, Jun-Hai; Xu, Feng; Panozzo, Daniele and Assarsson, Ulf
    3D gaze tracking from a single RGB camera is very challenging due to the lack of information in determining the accurate gaze target from a monocular RGB sequence. The eyes tend to occupy only a small portion of the video, and even small errors in estimated eye orientations can lead to very large errors in the triangulated gaze target. We overcome these difficulties with a novel lightweight eyeball calibration scheme that determines the user-specific visual axis, eyeball size and position in the head. Unlike the previous calibration techniques, we do not need the ground truth positions of the gaze points. In the online stage, gaze is tracked by a new gaze fitting algorithm, and refined by a 3D gaze regression method to correct for bias errors. Our regression is pre-trained on several individuals and works well for novel users. After the lightweight one-time user calibration, our method operates in real time. Experiments show that our technique achieves state-of-the-art accuracy in gaze angle estimation, and we demonstrate applications of 3D gaze target tracking and gaze retargeting to an animated 3D character.
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    Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Alexanderson, Simon; Henter, Gustav Eje; Kucherenko, Taras; Beskow, Jonas; Panozzo, Daniele and Assarsson, Ulf
    Automatic synthesis of realistic gestures promises to transform the fields of animation, avatars and communicative agents. In off-line applications, novel tools can alter the role of an animator to that of a director, who provides only high-level input for the desired animation; a learned network then translates these instructions into an appropriate sequence of body poses. In interactive scenarios, systems for generating natural animations on the fly are key to achieving believable and relatable characters. In this paper we address some of the core issues towards these ends. By adapting a deep learning-based motion synthesis method called MoGlow, we propose a new generative model for generating state-of-the-art realistic speech-driven gesticulation. Owing to the probabilistic nature of the approach, our model can produce a battery of different, yet plausible, gestures given the same input speech signal. Just like humans, this gives a rich natural variation of motion. We additionally demonstrate the ability to exert directorial control over the output style, such as gesture level, speed, symmetry and spacial extent. Such control can be leveraged to convey a desired character personality or mood. We achieve all this without any manual annotation of the data. User studies evaluating upper-body gesticulation confirm that the generated motions are natural and well match the input speech. Our method scores above all prior systems and baselines on these measures, and comes close to the ratings of the original recorded motions. We furthermore find that we can accurately control gesticulation styles without unnecessarily compromising perceived naturalness. Finally, we also demonstrate an application of the same method to full-body gesticulation, including the synthesis of stepping motion and stance.
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    Motion Retargetting based on Dilated Convolutions and Skeleton-specific Loss Functions
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Kim, SangBin; Park, Inbum; Kwon, Seongsu; Han, JungHyun; Panozzo, Daniele and Assarsson, Ulf
    Motion retargetting refers to the process of adapting the motion of a source character to a target. This paper presents a motion retargetting model based on temporal dilated convolutions. In an unsupervised manner, the model generates realistic motions for various humanoid characters. The retargetted motions not only preserve the high-frequency detail of the input motions but also produce natural and stable trajectories despite the skeleton size differences between the source and target. Extensive experiments are made using a 3D character motion dataset and a motion capture dataset. Both qualitative and quantitative comparisons against prior methods demonstrate the effectiveness and robustness of our method.
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    Real-time Anticipation of Occlusions for Automated Camera Control in Toric Space
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Burg, Ludovic; Lino, Christophe; Christie, Marc; Panozzo, Daniele and Assarsson, Ulf
    Efficient visibility computation is a prominent requirement when designing automated camera control techniques for dynamic 3D environments; computer games, interactive storytelling or 3D media applications all need to track 3D entities while ensuring their visibility and delivering a smooth cinematic experience. Addressing this problem requires to sample a large set of potential camera positions and estimate visibility for each of them, which in practice is intractable despite the efficiency of ray-casting techniques on recent platforms. In this work, we introduce a novel GPU-rendering technique to efficiently compute occlusions of tracked targets in Toric Space coordinates - a parametric space designed for cinematic camera control. We then rely on this occlusion evaluation to derive an anticipation map predicting occlusions for a continuous set of cameras over a user-defined time window. We finally design a camera motion strategy exploiting this anticipation map to minimize the occlusions of tracked entities over time. The key features of our approach are demonstrated through comparison with traditionally used ray-casting on benchmark scenes, and through an integration in multiple game-like 3D scenes with heavy, sparse and dense occluders.
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    Binary Ostensibly-Implicit Trees for Fast Collision Detection
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Chitalu, Floyd M.; Dubach, Christophe; Komura, Taku; Panozzo, Daniele and Assarsson, Ulf
    We present a simple, efficient and low-memory technique, targeting fast construction of bounding volume hierarchies (BVH) for broad-phase collision detection. To achieve this, we devise a novel representation of BVH trees in memory. We develop a mapping of the implicit index representation to compact memory locations, based on simple bit-shifts, to then construct and evaluate bounding volume test trees (BVTT) during collision detection with real-time performance. We model the topology of the BVH tree implicitly as binary encodings which allows us to determine the nodes missing from a complete binary tree using the binary representation of the number of missing nodes. The simplicity of our technique allows for fast hierarchy construction achieving over 6x speedup over the state-of-the-art. Making use of these characteristics, we show that not only it is feasible to rebuild the BVH at every frame, but that using our technique, it is actually faster than refitting and more memory efficient.
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    Efficient Minimum Distance Computation for Solids of Revolution
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Son, Sang-Hyun; Yoon, Seung-Hyun; Kim, Myung-Soo; Elber, Gershon; Panozzo, Daniele and Assarsson, Ulf
    We present a highly efficient algorithm for computing the minimum distance between two solids of revolution, each of which is defined by a planar cross-section region and a rotation axis. The boundary profile curve for the cross-section is first approximated by a bounding volume hierarchy (BVH) of fat arcs. By rotating the fat arcs around the axis, we generate the BVH of fat tori that bounds the surface of revolution. The minimum distance between two solids of revolution is then computed very efficiently using the distance between fat tori, which can be boiled down to the minimum distance computation for circles in the three-dimensional space. Our circle-based approach to the solids of revolution has distinctive features of geometric simplification. The main advantage is in the effectiveness of our approach in handling the complex cases where the minimum distance is obtained in non-convex regions of the solids under consideration. Though we are dealing with a geometric problem for solids, the algorithm actually works in a computational style similar to that of handling planar curves. Compared with conventional BVH-based methods, our algorithm demonstrates outperformance in computing speed, often 10-100 times faster. Moreover, the minimum distance can be computed very efficiently for the solids of revolution under deformation, where the dynamic reconstruction of fat arcs dominates the overall computation time and takes a few milliseconds.
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    Segment Tracing Using Local Lipschitz Bounds
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Galin, Eric; Guérin, Eric; Paris, Axel; Peytavie, Adrien; Panozzo, Daniele and Assarsson, Ulf
    We introduce Segment Tracing, a new algorithm that accelerates the classical Sphere Tracing method for computing the intersection between a ray and an implicit surface. Our approach consists in computing the Lipschitz bound locally over a segment to improve the marching step computation and accelerate the overall process. We describe the computation of the Lipschitz bound for different operators and primitives. We demonstrate that our algorithm significantly reduces the number of field function queries compared to previous methods, without the need for additional accelerating data-structures. Our method can be applied to a vast variety of implicit models ranging from hierarchical procedural objects built from complex primitives, to simulation-generated implicit surfaces created from many particles.
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    Robust Shape Collection Matching and Correspondence from Shape Differences
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Cohen, Aharon; Ben-Chen, Mirela; Panozzo, Daniele and Assarsson, Ulf
    We propose a method to automatically match two shape collections with a similar shape space structure, e.g. two characters in similar poses, and compute the inter-maps between the collections. Given the intra-maps in each collection, we extract the corresponding shape difference operators, and use them to construct an embedding of the shape space of each collection. We then align the two shape spaces, and use the knowledge gained from the alignment to compute the inter-maps. Unlike existing approaches for collection alignment, our method is applicable to small and large collections alike, and requires no parameter tuning. Furthermore, unlike most approaches for non-isometric correspondence, our method uses solely the variation within the collection to extract the inter-maps, and therefore does not require landmarks, descriptors or any additional input. We demonstrate that we achieve high matching accuracy rates, and compute high quality maps on non-isometric shapes, which compare favorably with automatic state-of-the-art methods for non-isometric shape correspondence.
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    Displacement-Correlated XFEM for Simulating Brittle Fracture
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Chitalu, Floyd M.; Miao, Qinghai; Subr, Kartic; Komura, Taku; Panozzo, Daniele and Assarsson, Ulf
    We present a remeshing-free brittle fracture simulation method under the assumption of quasi-static linear elastic fracture mechanics (LEFM). To achieve this, we devise two algorithms. First, we develop an approximate volumetric simulation, based on the extended Finite Element Method (XFEM), to initialize and propagate Lagrangian crack-fronts. We model the geometry of fracture explicitly as a surface mesh, which allows us to generate high-resolution crack surfaces that are decoupled from the resolution of the deformation mesh. Our second contribution is a mesh cutting algorithm, which produces fragments of the input mesh using the fracture surface. We do this by directly operating on the half-edge data structures of two surface meshes, which enables us to cut general surface meshes including those of concave polyhedra and meshes with abutting concave polygons. Since we avoid triangulation for cutting, the connectivity of the resulting fragments is identical to the (uncut) input mesh except at edges introduced by the cut. We evaluate our simulation and cutting algorithms and show that they outperform state-of-the-art approaches both qualitatively and quantitatively.
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    Interactive Meso-scale Simulation of Skyscapes
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Vimont, Ulysse; Gain, James; Lastic, Maud; Cordonnier, Guillaume; Abiodun, Babatunde; Cani, Marie-Paule; Panozzo, Daniele and Assarsson, Ulf
    Although an important component of natural scenes, the representation of skyscapes is often relatively simplistic. This can be largely attributed to the complexity of the thermodynamics underpinning cloud evolution and wind dynamics, which make interactive simulation challenging.We address this problem by introducing a novel layered model that encompasses both terrain and atmosphere, and supports efficient meteorological simulations. The vertical and horizontal layer resolutions can be tuned independently, while maintaining crucial inter-layer thermodynamics, such as convective circulation and land-air transfers of heat and moisture. In addition, we introduce a cloud-form taxonomy for clustering, classifying and upsampling simulation cells to enable visually plausible, finely-sampled volumetric rendering. As our results demonstrate, this pipeline allows interactive simulation followed by up-sampled rendering of extensive skyscapes with dynamic clouds driven by consistent wind patterns. We validate our method by reproducing characteristic phenomena such as diurnal shore breezes, convective cells that contribute to cumulus cloud formation, and orographic effects from moist air driven upslope.
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    Simulation of Dendritic Painting
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Canabal, José A.; Otaduy, Miguel A.; Kim, Byungmoon; Echevarria, Jose; Panozzo, Daniele and Assarsson, Ulf
    We present a new system for interactive dendritic painting. Dendritic painting is characterized by the unique and intricate branching patterns that grow from the interaction of inks, solvents and medium. Painting sessions thus become very dynamic and experimental. To achieve a compelling simulation of this painting technique we introduce a new Reaction-Diffusion model with carefully designed terms to allow natural interactions in a painting context. We include additional user control not possible in the real world to guide and constrain the growth of the patterns in expressive ways. Our multi-field model is able to capture and simulate all these complex phenomena efficiently in real time, expanding the tools available to the digital artist, while producing compelling animations for motion graphics.