DeepFake Detection using Fused Convolutional Neural Network Predictions

Deepfakes are synthetically generated images, videos or audios, which fraudsters use to manipulate legitimate information. The proposed technique outperforms state-of-the-art models with 96.5% accuracy, when tested on publicly available DeepFake Detection Challenge (DFDC) test data, comprising of 400 videos.

Data and Resources

Cite this as

Sohail Ahmed Khan, Dr. Alessandro Artusi, Dr. Hang Dai (2024). Dataset: DeepFake Detection using Fused Convolutional Neural Network Predictions. https://doi.org/10.57702/9ducaxsk

DOI retrieved: December 17, 2024

Additional Info

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Created December 17, 2024
Last update December 17, 2024
Defined In https://doi.org/10.48550/arXiv.2102.05950
Author Sohail Ahmed Khan
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Dr. Alessandro Artusi
Dr. Hang Dai
Homepage https://arxiv.org/abs/2006.07397