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ADGD '21: Proceedings of the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection
ACM2021 Proceeding
  • Program Chairs:
  • Stefan Winkler,
  • Weiling Chen,
  • Abhinav Dhall,
  • Pavel Korshunov
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
MM '21: ACM Multimedia Conference Virtual Event China 24 October 2021
ISBN:
978-1-4503-8682-1
Published:
20 October 2021
Sponsors:
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Abstract

It is our great pleasure to welcome you to the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection (ADGD 2021). The purpose of the workshop is to provide a platform for researchers and engineers to share their ideas and approaches on fake media generation and detection.

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SESSION: Keynote Talk
keynote
Fighting AI-synthesized Fake Media

Recent years have witnessed an unexpected and astonishing rise of AI-synthesized fake media (GAN synthesized faces, face-swap videos, and style transferred audios, commonly known as the DeepFakes), thanks to the rapid advancement of technology and the ...

keynote
Representations for Content Creation, Manipulation and Animation

What I cannot create, I do not understand" said the famous writing on Dr. Feynman's blackboard. The ability to create or to change objects requires us to understand their structure and factors of variation. For example, to draw a face an artist is ...

keynote
"Deepfake" Portrait Image Generation

With the prevailing of deep learning technology, especially generative adversarial networks (GAN), generating photo-realistic facial images has made huge progress. Image generation techniques have many good applications such as data augmentation, ...

SESSION: Session 1: Deepfake Detection
research-article
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors

Significant advancements made in the generation of deepfakes have caused security and privacy issues. Attackers can easily impersonate a person's identity in an image by replacing his face with the target person's face. Moreover, a new domain of cloning ...

research-article
DmyT: Dummy Triplet Loss for Deepfake Detection

Recent progress in deep learning-based image generation has madeit easier to create convincing fake videos called deepfakes. Whilethe benefits of such technology are undeniable, it can also be usedas realistic fake news support for mass disinformation. ...

SESSION: Session 2: Deepfake Generation
research-article
Invertable Frowns: Video-to-Video Facial Emotion Translation

We present Wav2Lip-Emotion, a video-to-video translation architecture that modifies facial expressions of emotion in videos of speakers. Previous work modifies emotion in images, uses a single image to produce a video with animated emotion, or puppets ...

Contributors
  • AI Singapore
  • Flinders University
  • Institut Dalle Molle D'intelligence Artificielle Perceptive
  1. Proceedings of the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection

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