WORKSHOP ON SYNTHETIC MULTIMEDIA - AUDIOVISUAL DEEPFAKE GENERATION AND DETECTION
Motivation

The development of powerful deep learning technologies has also brought about some negative effects. One such issue is the emergence of deepfakes. While most work has focused on fake images and video alone, the multi-modal, audiovisual aspect is very important to both convincing generation and accurate detection of fake multimedia content. In addition to developing accurate and robust detection models, it is worthwhile to explore fake media generation methods as well. Content generation has many meaningful and beneficial applications, such as commercial ads, education, privacy protection, etc. Therefore, fake media generation constitutes an integral component of the proposed workshop. The purpose of the workshop is to provide a platform for researchers and engineers to share their ideas and approaches, and give some insights on fake media generation and detection to both academia and industry.

Invitation

We invite submissions on a range of AI technologies and applications for media forensics domains. Topics of interest include but are not limited to the following:

  • Fake image generation and/or detection
  • Fake voice generation and/or detection
  • Audiovisual Deepfakes and adversarial attacks
  • Audiovisual Deepfakes and Fairness and Ethics
  • Audiovisual Deepfakes and Data augmentation
  • Audiovisual Deepfake datasets
Important Dates
  • Paper Submission Deadline: August 10th 2021
  • Notification of Acceptance: August 26th 2021
  • Camera-Ready: September 2nd 2021
  • Workshop: October
Programme

TBD

Contact Us

If you have any queries, please email us at adgd2021@aisingapore.org

CMT Submission Website is available now at
https://cmt3.research.microsoft.com/ACMMM2021

Please choose "Track: 1st Workshop on Synthetic Multimedia – Audiovisual Deepfake Generation and Detection" to submit your workshop paper.

Submissions should follow the ACM Multimedia 2021 format and comprise 6 to 8 pages (refer to the template here: https://www.acm.org/publications/proceedings-template), with up to two additional pages for references.

Stefan Winkler is Senior Deputy Director at AI Singapore and Associate Professor (Practice) at the National University of Singapore. Prior to that he was Distinguished Scientist and Director of the Video & Analytics Program at the University of Illinois’ Advanced Digital Sciences Center (ADSC) in Singapore. He also co-founded two start-ups and worked for a Silicon Valley company. Dr. Winkler has a Ph.D. degree from the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and a Dipl.-Ing. (M.Eng./B.Eng.) degree from the University of Technology Vienna, Austria. He is an IEEE Fellow and has published over 150 papers. He has also contributed to international standards in VQEG, ITU, ATIS, VSF, and SCTE.

Weiling Chen is Senior AI Engineer at AI Singapore and National University of Singapore. Prior to that she was Data Scientist at Lazada Group. She received her Ph.D degree from Nanyang Technological University and B.Eng. in Computer Science and Technology from Shandong University. She has won Champion for SeeTrue Workshop organized by Defence Science and Technology Agency (DSTA).

Abhinav Dhall is a lecturer and co-director of the Human-Centred Artificial Intelligence lab at Monash University. He is also an Assistant Professor (on leave) at the Indian Institute of Technology Ropar. He received his Ph.D. degree from the Australian National University. His research has received awards at ACM ICMR, IEEE FG and IEEE ICME.

Dr. Pavel Korshunov is a research associate at the Idiap Research Institute (Martigny, Switzerland). He currently works on detection of deepfakes and audio-visual manipulations, age detection in images and voice, and speech anti-spoofing. He received Ph.D. in Computer Science from School of Computing, National University of Singapore in 2011 and was a postdoctoral researcher at EPFL (Lausanne, Switzerland) and Idiap Research Institute. During his past tenures, he worked on problems related to high dynamic range(HDR) imaging, crowdsourcing, visual privacy in video surveillance.He has over 70 papers with one ACM TOMM journal best paper award(2011), two top 10% best paper awards in MMSP 2014, and a top 10% best paper awards in ICIP 2014. He is also a co- editor of JPEG XT standard for HDR images.

This research is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG-RP-2019-050).
Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.
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