Dual Attention Network Approaches to Face Forgery Video Detection

Dual Attention Network Approaches to Face Forgery Video Detection

Forged videos are commonly spread online. Most have malicious content and cause serious information security problems. The most critical issue in deepfake detection is the identification of traces of tampering in fake videos. This study designs a Dual Attention Forgery Detection Network (DAFDN), whi...

Full description

Bibliographic Details
Main Authors: Yi-Xiang Luo, Jiann-Liang Chen
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deepfake
forgery video detection
dual attention neural network
convolutional neural network
information security
Online Access:https://ieeexplore.ieee.org/document/9925231/

Internet

https://ieeexplore.ieee.org/document/9925231/

Similar Items