DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

4 被引用数 (Scopus)

抄録

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors. Motivated by the fact that remote visual photoplethysmography (PPG) is made possible by monitoring the minuscule periodic changes of skin color due to blood pumping through the face, we conjecture that normal heartbeat rhythms found in the real face videos will be disrupted or even entirely broken in a DeepFake video, making it a potentially powerful indicator for DeepFake detection. In this work, we propose DeepRhythm, a DeepFake detection technique that exposes DeepFakes by monitoring the heartbeat rhythms. DeepRhythm utilizes dual-spatial-temporal attention to adapt to dynamically changing face and fake types. Extensive experiments on FaceForensics++ and DFDC-preview datasets have confirmed our conjecture and demonstrated not only the effectiveness, but also the generalization capability of DeepRhythm over different datasets by various DeepFakes generation techniques and multifarious challenging degradations.

本文言語英語
ホスト出版物のタイトルMM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
出版社Association for Computing Machinery, Inc
ページ1318-1327
ページ数10
ISBN(電子版)9781450379885
DOI
出版ステータス出版済み - 10 12 2020
イベント28th ACM International Conference on Multimedia, MM 2020 - Virtual, Online, 米国
継続期間: 10 12 202010 16 2020

出版物シリーズ

名前MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia

会議

会議28th ACM International Conference on Multimedia, MM 2020
国/地域米国
CityVirtual, Online
Period10/12/2010/16/20

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 人間とコンピュータの相互作用

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