Generalization of Forgery Detection With Meta Deepfake Detection Model

Author:

Tran Van-Nhan1ORCID,Kwon Seong-Geun2,Lee Suk-Hwan3,Le Hoanh-Su4,Kwon Ki-Ryong1ORCID

Affiliation:

1. Department of Artificial Intelligence Convergence, Pukyong National University, Busan, South Korea

2. Department of Electronics Engineering, Kyungil University, Gyeongsan, South Korea

3. Department of Computer Engineering, Dong-A University, Busan, South Korea

4. Faculty of Information Systems, University of Economics and Law, Vietnam National University Ho Chi Minh City, Ho Chi Minh, Vietnam

Funder

Basic Science Research Program through the National Research Foundation of Korea

Ministry of Education

Ministry of Science and ICT (MSIT), South Korea, through the Information Technology Research Center (ITRC) Support Program

Institute for Information & Communications Technology Planning & Evaluation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference63 articles.

1. Celeb-DF: A Large-Scale Challenging Dataset for DeepFake Forensics

2. Combining EfficientNet and Vision Transformers for Video Deepfake Detection

3. The DeepFake detection challenge (DFDC) dataset;dolhansky;arXiv 2006 07397,2020

4. Random Erasing Data Augmentation

5. Unsupervised learning via meta-learning;hsu;arXiv 1810 02334,2018

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