DFDT: An End-to-End DeepFake Detection Framework Using Vision Transformer

DFDT: An End-to-End DeepFake Detection Framework Using Vision Transformer

The ever-growing threat of deepfakes and large-scale societal implications has propelled the development of deepfake forensics to ascertain the trustworthiness of digital media. A common theme of existing detection methods is using Convolutional Neural Networks (CNNs) as a backbone. While CNNs have...

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Bibliographic Details
Main Authors: Aminollah Khormali, Jiann-Shiun Yuan
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Applied Sciences
Subjects:
cybersecurity
deep learning
deepfake detection
vision transformer
Online Access:https://www.mdpi.com/2076-3417/12/6/2953

Internet

https://www.mdpi.com/2076-3417/12/6/2953

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