Improving GAN-Generated Image Detection Generalization Using Unsupervised Domain Adaptation

Author:

Zhang Mingxu1,Wang Hongxia1,He Peisong1,Malik Asad2,Liu Hanqing1

Affiliation:

1. School of Cyber Science and Engineering, Sichuan University,Chengdu,China

2. Aligarh Muslim University,Department of Computer Science,Aligarh,India

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

IEEE

Reference22 articles.

1. Global Texture Enhancement for Fake Face Detection in the Wild

2. Do GANs leave artificial finger-prints?;marra;IEEE Conference on Multimedia Information Processing and Retrieval,0

3. De-tecting and simulating artifacts in GAN fake images;zhang;IEEE International Workshop on Information Forensics and Security,0

4. CNN-Generated Images Are Surprisingly Easy to Spot… for Now

5. Detecting CNN-Generated Facial Images in Real-World Scenarios

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1. Research on High-Fidelity License Plates Generated Using Generative Adversarial Network (GAN) Technology for Vehicle Recognition Systems;Proceedings of the 2024 13th International Conference on Software and Computer Applications;2024-02

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4. Using Generative Adversarial Network Technology for Repairing Dynamically Blurred License Plates;2023 Sixth International Symposium on Computer, Consumer and Control (IS3C);2023-06

5. Global–Local Facial Fusion Based GAN Generated Fake Face Detection;Sensors;2023-01-05

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