skip to main content
research-article
Free Access

Beyond Deep Fakes

Authors Info & Claims
Published:22 September 2023Publication History
Skip Abstract Section

Abstract

A conceptual framework and research agenda for neural rendering of realistic digital faces.

References

  1. Agarwal, S. et al. Protecting world leaders against deep fakes. CVPR Workshop (2019), 38--45.Google ScholarGoogle Scholar
  2. Bradley, S. Even better than the real thing? Meet the virtual influencers taking over your feeds. The Drum (2020); https://bit.ly/3YD06k2.Google ScholarGoogle Scholar
  3. Debevec, P. et al. Acquiring the reflectance field of a human face. In Proceedings of the ACM Siggraph 2000, 145--156.Google ScholarGoogle Scholar
  4. Goodfellow, I. et al. Generative adversarial nets. Mining of Massive Datasets 2nd Ed. (2014) Google ScholarGoogle ScholarCross RefCross Ref
  5. Karras, T., Laine, S., and Aila, T. A. style-based generator architecture for generative adversarial networks. CVPR (2019).Google ScholarGoogle Scholar
  6. Kulkarni, T.D., Whitney, W.F., Kohli, P., and Tenenbaum, J.B. Deep convolutional inverse graphics network. In Proceedings of the 28th Intern. Conf. on Neural Information Processing Systems 2 (Dec. 2015), 2539--2547.Google ScholarGoogle Scholar
  7. Leo, M.J. and Manimegalai, D. 3D modeling of human faces---A survey. In Proceedings of the 3rd Intern. Conf. Trendz in Information Sciences & Computing (2011), 40--45 Google ScholarGoogle ScholarCross RefCross Ref
  8. Mitchell, V. Salesforce Ventures part of US$40 million investment into Soul Machines. CMO Australia (Jan. 10, 2020); https://bit.ly/44mnWC4.Google ScholarGoogle Scholar
  9. Naruniec, J., Helminger, L., Schroers, C., and R.M., Weber. High-resolution neural face swapping for visual effects. In Proceedings of the Eurographics Symp. on Rendering 30 (2020), 1--15.Google ScholarGoogle ScholarCross RefCross Ref
  10. Seymour, M., Riemer, K., and Kay, J. Actors, avatars and agents: Potentials and implications of natural face technology for the creation of realistic visual presence. J. Assoc. Information Systems 19, 10 (2018).Google ScholarGoogle Scholar
  11. Seymour, M. Deep neural rendering comes of age. fxguide (Dec. 16, 2021); https://bit.ly/3OWtbnj.Google ScholarGoogle Scholar
  12. Seymour, M. et al. Facing the artificial: Understanding affinity, trustworthiness, and preference for more realistic digital humans. In Proceedings of the 53rd Hawaii Intern. Conf. System Sciences 3, (2020), 4673--4683.Google ScholarGoogle ScholarCross RefCross Ref
  13. Seymour, M. The neural rendering of the champion. fxguide (2022); https://bit.ly/44h8PcV.Google ScholarGoogle Scholar
  14. Shieber, J. More investors are betting on virtual influencers like Lil Miquela. TechCrunch (Jan. 14, 2019); https://tcrn.ch/44dJrVm.Google ScholarGoogle Scholar
  15. Stone, L. Partnership on AI, Kodiak Robotics, Faraday Future, more take out PPP loans. AI Business (2020); https://bit.ly/3OHzIRq.Google ScholarGoogle Scholar
  16. Takahashi, D. Wave raises $30 million for superstars to stage virtual concerts | VentureBeat (2020); https://bit.ly/45ubL71.Google ScholarGoogle Scholar
  17. Tewari, A. et al. State of the art on neural rendering. In Proceedings of the Computer Graphics Forum (2020).Google ScholarGoogle Scholar
  18. Tian, G., Yuan, Y., and Liu, Y. Audio2Face: Generating speech/face animation from single audio with attention-based bidirectional LSTM networks. In Proceedings of the 2019 IEEE Intern. Conf. Multimedia Expo Workshop, 366--371 (2019) Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Beyond Deep Fakes

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image Communications of the ACM
            Communications of the ACM  Volume 66, Issue 10
            October 2023
            110 pages
            ISSN:0001-0782
            EISSN:1557-7317
            DOI:10.1145/3625456
            • Editor:
            • James Larus
            Issue’s Table of Contents

            Copyright © 2023 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 22 September 2023

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article
          • Article Metrics

            • Downloads (Last 12 months)6,825
            • Downloads (Last 6 weeks)173

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          HTML Format

          View this article in HTML Format .

          View HTML Format