Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors-Reference-Cited by-同舟云学术

Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors

Published:2021-10-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection
language:
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Author:

Khalid Hasam¹,Kim Minha¹,Tariq Shahroz¹,Woo Simon S.¹

Affiliation:

1. Sungkyunkwan University, Suwon, Republic of Korea

Funder

National Research Foundation of Korea (NRF) grant funded by Korea government MSIT Basic Science Research Program

IITP grant funded by the Korea government (MSIT) AI Graduate School Support Program

MSIT (Ministry of Science ICT) Korea under the High-Potential Individuals Global Training Program

IITP grant funded by the Korea government MSITOriginal Technology Development of Artificial Intelligence Industry

IITP grant funded by the Korea government (MSIT) Regional strategic industry convergence security core talent training business

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3476099.3484315

Reference96 articles.

1. MesoNet: a Compact Facial Video Forgery Detection Network

2. Deepfake Video Detection through Optical Flow Based CNN

3. APTLY lab. 2020. The Fake-or-Real Dataset. http://bil.eecs.yorku.ca/datasets/ [Online; accessed 28-July-2021]. APTLY lab. 2020. The Fake-or-Real Dataset. http://bil.eecs.yorku.ca/datasets/ [Online; accessed 28-July-2021].

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