Detecting Compressed Deepfake Images Using Two-Branch Convolutional Networks with Similarity and Classifier
As a popular technique for swapping faces with someone else’s in images or videos through deep neural networks, deepfake causes a serious threat to the security of multimedia content today. However, because counterfeit images are usually compressed when propagating over the Internet, and because the...
Main Authors: | Ping Chen, Ming Xu, Xiaodong Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Symmetry |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-8994/14/12/2691 |
Similar Items
-
Multi-Feature Fusion Based Deepfake Face Forgery Video Detection
by: Zhimao Lai, et al.
Published: (2022-03-01) -
Fighting Deepfakes by Detecting GAN DCT Anomalies
by: Oliver Giudice, et al.
Published: (2021-07-01) -
Deepfake Video Detection Based on MesoNet with Preprocessing Module
by: Zhiming Xia, et al.
Published: (2022-05-01) -
Lip forgery detection via spatial-frequency domain combination
by: Jiaying LIN, Wenbo ZHOU, Weiming ZHANG, Nenghai YU
Published: (2022-12-01) -
Multi-attention-based approach for deepfake face and expression swap detection and localization
by: Saima Waseem, et al.
Published: (2023-08-01)