BMNet: Enhancing Deepfake Detection Through BiLSTM and Multi-Head Self-Attention Mechanism

BMNet: Enhancing Deepfake Detection Through BiLSTM and Multi-Head Self-Attention Mechanism

When forgery techniques can generate highly realistic videos, traditional convolutional neural network (CNN)-based detection models often struggle to capture subtle forgery features and temporal dependencies. Most existing models focus on feature extraction from static frames, neglecting the tempora...

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Bibliographic Details
Main Authors: Demao Xiong, Zhan Wen, Cheng Zhang, Dehao Ren, Wenzao Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deepfake
deepfake video detection
bi-directional long short-term memory network
multi-head self-attention mechanism
Online Access:https://ieeexplore.ieee.org/document/10852294/
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