Accepted Papers

  1. A Scriptable Tool for Photo Realistic Synthetic Image Generation
    Nathan Morrical (NVIDIA); Jonathan Tremblay (NVIDIA)*; Yunzhi Lin (Georgia Institute of Technology); Stephen Tyree (NVIDIA); Valerio Pascucci (University of Utah); Stan Birchfield (NVIDIA); Ingo Wald (NVIDIA) (PDF)
  2. Privacy-preserving object detection
    Peiyang He (University of Oxford); Krzysztof Kacprzyk (University of Oxford); Artjom S Joosen (University of Oxford); Michael Collyer (University of Oxford); Charlie J Griffin (University of Oxford); Aleksandar Shtedritski (University of Oxford); Yuki M Asano (University of Oxford)* (PDF)
  3. Imperfect ImaGANation: Implications of GANs Exacerbating Biases on Facial Data
    Niharika Jain (Arizona State University); Alberto Olmo (Arizona State University)*; Sailik Sengupta (Arizona State University); Lydia Manikonda (Rensselaer Polytechnic Institute); Subbarao Kambhampati (Arizona State University) (PDF)
  4. Differentially Private Query Release Through Adaptive Projection
    Sergul Aydore (Amazon Web Services)*; William Brown (Columbia University); Michael Kearns (University of Pennsylvania); Krishnaram Kenthapadi (Amazon); Luca Melis (Amazon Web Services); Aaron Roth (University of Pennsylvania); Ankit A Siva (Amazon) (PDF)
  5. Bayesian Perspective on Visual Data Augmentation for Efficient Utilization of Sub-sampled Data
    Joonhyun Jeong (Clova Face, NAVER Corp.); Sungmin Cha (Sungkyunkwan University); Youngjoon Yoo (Clova AI Research, NAVER Corp.)*; Sangdoo Yun (NAVER AI LAB); Jongwon Choi (Chung-Ang University) (PDF)
  6. One-Shot GAN: Learning to Generate Samples from Single Images and Videos
    Vadim Sushko (Bosch Center for Artificial Intelligence)*; Jürgen Gall (University of Bonn); Anna Khoreva (Bosch Center for Artificial Intelligence) (PDF)
  7. You Only Need Adversarial Supervision for Semantic Image Synthesis
    Edgar Schoenfeld (Bosch Center for Artificial Intelligence, Germany); Vadim Sushko (Bosch Center for Artificial Intelligence)*; Dan Zhang (Bosch Center for Artificial Intelligence); Jurgen Gall (University of Bonn); Bernt Schiele (MPI Informatics); Anna Khoreva (Bosch Center for Artificial Intelligence) (PDF)
  8. Synthetic data for model selection
    Matan Fintz (Amazon); Alon Shoshan (Technion)*; Nadav Bhonker (Amazon); Igor Kviatkovsky (Amazon); gerard medioni (USC) (PDF)
  9. Ensembles of GANs for synthetic training data generation
    Gabriel Eilertsen (Linköping University)*; Apostolia Tsirikoglou (Linköping University); Claes Lundström (Linköping University); Jonas Unger (Linköpings universitet) (PDF)
  10. Leveraging Public Data for Practical Private Query Release
    Terrance Liu (Carnegie Mellon University)*; Giuseppe Vietri (University of Minnesota); Thomas Steinke (); Jonathan Ullman (Northeastern University); Steven Wu (Carnegie Mellon University) (PDF)
  11. FFPDG: Fast, Fair and Private Data Generation
    Weijie Xu (Amazon)*; Jinjin Zhao (Amazon ); Francis Iannacci (Amazon); Bo Wang (Amazon) (PDF)
  12. Improving Augmentation and Evaluation Schemes for Semantic Image Synthesis
    Prateek Katiyar (Bosch Center for Artificial Intelligence)*; Anna Khoreva (Bosch Center for Artificial Intelligence) (PDF)
  13. Towards creativity characterization of generative models via group-based subset scanning
    Celia Cintas (IBM Research Africa)*; Payel Das (IBM Research); Brian Quanz (IBM Research); Skyler D Speakman (IBM Research); Victor Akinwande (IBM Research); Pin-Yu Chen (IBM Research) (PDF)
  14. Transitioning from Real to Synthetic data: Quantifying the bias in model
    Aman Gupta (Mastercard)*; Deepak Bhatt (Mastercard); Anubha Pandey (Mastercard) (PDF)
  15. Few-shot learning via tensor hallucination
    Michalis ML Lazarou (Imperial College London)*; Tania Stathaki (Imperial College London); Yannis Avrithis (Inria) (PDF)
  16. Unconditional Synthesis of Complex Scenes Using a semantic bottleneck
    Samaneh Azadi (University of California Berkeley )*; Michael Tschannen (Apple); Eric Tzeng (UC Berkeley); Sylvain Gelly (Google Brain); Trevor Darrell (UC Berkeley); Mario Lucic (Google Brain) (PDF)
  17. Evaluating the Quality of Synthetic Images of Porous Media: A Morphological and Physics-Based Approach
    Kelly Guan (Stanford University)*; Anthony Kovscek (Stanford University); Timothy Anderson (Stanford University); Patrice Creux (Universite de Pau et des Pays de l'Adour) (PDF)
  18. Joint Text and Label Generation for Spoken Language Understanding
    Yang Li (Department of Computer Science, University of North Carolina at Chapel Hill)*; Ben Athiwaratkun (Cornell University); Cicero Nogueira dos Santos (Amazon Web Services); Bing Xiang (Amazon) (PDF)
  19. Extremely Private Supervised Learning
    Armand Lacombe (Inria)*; Saumya Jetley (Inria); Michele Sebag (LRI, CNRS, France) (PDF)
  20. Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation
    August DuMont Schütte (Max Planck Institute for Intelligent Systems)*; Jürgen Hetzel (University Hospital of Tübingen); Sergios Gatidis (University of Tübingen); Tobias Hepp (Max Planck Institute for Intelligent Systems); Benedikt Dietz (ETH Zurich); Stefan Bauer (Max Planck institute); Patrick Schwab (ETH Zurich) (PDF)
  21. PrivSyn: Differentially Private Data Synthesis
    Zhikun Zhang (CISPA Helmholtz Center for Information Security)*; Tianhao Wang (Purdue University); Ninghui Li (Purdue University); Jean Honorio (Purdue); Michael Backes (CISPA Helmholtz Center for Information Security); Shibo He (Zhejiang University); Jiming Chen (Zhejiang University); Yang Zhang (CISPA) (PDF)
  22. Privacy-preserving High-dimensional Data Collection with Federated Generative Autoencoder
    Xue Jiang (Technische Universität München)*; Xuebing Zhou (Huawei Technologies Düsseldorf GmbH); Jens Grossklags (Technische Universität München) (PDF)
  23. What if I don't have in-domain unlabeled data for Semi-Supervised Learning? Well, generate some!
    Xuanli He ( Monash University)*; Islam H Nassar (Monash University); Jamie Kiros (Google); Reza Haffari (Monash University, Australia); Mohammad Norouzi (Google Research, Brain Team) (PDF)
  24. Representative & Fair Synthetic Data
    Paul Tiwald (Mostly AI)*; Alexandra Ebert (MOSTLY AI); Daniel T Soukup (Independent Researcher) (PDF)