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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10852294/ |
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