Eurographics Symposium on Rendering 2020 – DL-only Track –
London, UK 29 June - 3 July 2020
Organized by
EUROGRAPHICS THEEUROPEANASSOCIATION
FORCOMPUTERGRAPHICS
Program Co-Chairs
Carsten Dachsbacher, Karlsruhe Institute of Technology (KIT), Germany Matt Pharr, NVIDIA, USA
Conference Co-Chairs
Abhijeet Ghosh, Imperial College London, UK Tobias Ritschel, University College London, UK
Tim Weyrich, University College London, UK
Proceedings Production Editor
Dieter Fellner (TU Darmstadt & Fraunhofer IGD, Germany) Sponsored by EUROGRAPHICS Association
DOI: 10.2312/sr.20202013 https://www.eg.org https://diglib.eg.org
This work is subject to copyright.
All rights reserved, whether the whole or part of the material is concerned, specifically those of translation, reprinting, re-use of illustrations, broadcasting, reproduction by photocopying machines or similar means, and storage in data banks.
Copyright ©2020 by the Eurographics Association Postfach 2926, 38629 Goslar, Germany
Published by the Eurographics Association –Postfach 2926, 38629 Goslar, Germany–
in cooperation with
Institute of Computer Graphics & Knowledge Visualization at Graz University of Technology and
Fraunhofer IGD (Fraunhofer Institute for Computer Graphics Research), Darmstadt ISBN 978-3-03868-117-5
ISSN 1727-3463
The electronic version of the proceedings is available from the Eurographics Digital Library at https://diglib.eg.org
Table of Contents
Table of Contents . . . iii
Sponsors . . . iv
International Programme Committee . . . v
Author Index . . . vi
Keynote . . . vii
Denoising and Filtering Temporal Normal Distribution Functions . . . 1
Lorenzo Tessari, Johannes Hanika, Carsten Dachsbacher, and Marc Droske Real-time Monte Carlo Denoising with the Neural Bilateral Grid . . . 13
Xiaoxu Meng, Quan Zheng, Amitabh Varshney, Gurprit Singh, and Matthias Zwicker Natural Appearance Multi-Scale Appearance Modeling of Granular Materials with Continuously Varying Grain Properties . . . 25
Cheng Zhang and Shuang Zhao Path Guiding Temporal Sample Reuse for Next Event Estimation and Path Guiding for Real-Time Path Tracing . . . 39
Addis Dittebrandt, Johannes Hanika, and Carsten Dachsbacher BxDFs Joint SVBRDF Recovery and Synthesis From a Single Image using an Unsupervised Generative Adversarial Network . . . 53 Yezi Zhao, Beibei Wang, Yanning Xu, Zheng Zeng, Lu Wang, and Nicolas Holzschuch
Sponsors
International Programme Committee Miika Aittala, NVIDIA, Finland
Tamy Boubekeur, Adobe, France Rachel Brown, NVIDIA, USA Yue Dong, MSR, China
George Drettakis, INRIA, France Philip Dutré, KU Leuven, Belgium Elmar Eisemann, TU Delft, Netherlands Elena Garces, Technicolor, France Iliyan Georgiev, Solid Angle, UK
Toshiya Hachisuka, University Tokyo, Japan Eric Heitz, Unity, France
Nicolas Holzschuch, INRIA, France Wojciech Jarosz, Dartmouth, USA
Nima Kalantari, Texas A&M University, USA Anton Kaplanyan, Facebook, USA
Jaakko Lehtinen, Aalto University and NVIDIA, Finland Hendrik Lensch, Tübingen University, Germany
Tzu-Mao Li, MIT, USA Steve Marschner, Cornell, USA
Belen Masia, Universitiy Zaragoza, Spain Diego Nehab, IMPA, Brazil
Jan Novak, NVIDIA, Switzerland Derek Nowrouzezahrai, McGill, Canada
Marta Ortín Obón, University of Zaragoza, Spain Pieter Peers, College of William & Mary, USA Fabio Pellacini, Sapienza University of Rome, Italy Christoph Peters, KIT, Germany
Jeppe Revall Frisvad, Technical University of Denmark, Denmark Holly Rushmeier, Yale University, USA
Pedro Sander, Hong Kong, China Peter-Pike Sloan, Activision, USA
Laszlo Szirmay-Kalos, Budapest University of Technology and Economics, Hungary Karthik Vaidyanathan, Intel, USA
Li-Yi Wei, Univ. of Hong Kong, Hong Kong Andrea Weidlich, Weta Digital, NZ
Michael Wimmer, TU Wien, Austria Hongzhi Wu, Zhejiang University, China Kun Xu, Tsinghua University, China Lingqi Yan, UC Santa Barbara, USA Sung-Eui Yoon, KAIST, South Korea Kun Zhou, Zhejiang University, China
Matthias Zwicker, University of Maryland, USA
Author Index Dachsbacher, Carsten . . . 1, 39
Dittebrandt, Addis . . . 39
Droske, Marc . . . 1
Hanika, Johannes . . . 1, 39 Holzschuch, Nicolas . . . 53
Meng, Xiaoxu . . . 13
Singh, Gurprit . . . 13
Tessari, Lorenzo . . . 1
Varshney, Amitabh . . . 13
Wang, Beibei . . . 53
Wang, Lu . . . 53
Xu, Yanning . . . 53
Zeng, Zheng . . . 53
Zhang, Cheng . . . 25
Zhao, Shuang . . . 25
Zhao, Yezi . . . 53
Zheng, Quan . . . 13
Zwicker, Matthias . . . 13
Keynote
Generative Models for Image Synthesis
Jan Kautz
Short Biography
Jan Kautz is VP of Learning and Perception Research at NVIDIA. Jan and his team pursue fundamental research in the areas of computer vision and deep learning, including visual perception, geometric vision, generative mod- els, and efficient deep learning. His and his team’s work has been recognized with various awards and has been regularly featured in the media. Before joining NVIDIA in 2013, Jan was a tenured faculty member at University College London. He holds a BSc in Computer Science from the University of Erlangen-Nürnberg (1999), an MMath from the University of Waterloo (1999), received his PhD from the Max-Planck-Institut für Informatik (2003), and worked as a post-doctoral researcher at the Massachusetts Institute of Technology (2003-2006).
