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• W3037967553 abstract "Better generative models and larger datasets have led to more realistic fake videos that can fool the human eye but produce temporal and spatial artifacts that deep learning approaches can detect. Most current Deepfake detection methods only use individual video frames and therefore fail to learn from temporal information. We created a benchmark of the performance of spatiotemporal convolutional methods using the Celeb-DF dataset. Our methods outperformed state-of-the-art frame-based detection methods. Code for our paper is publicly available at this https URL." @default.
• W3037967553 created "2020-07-02" @default.
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• W3037967553 date "2020-06-26" @default.
• W3037967553 modified "2023-09-27" @default.
• W3037967553 title "Deepfake Detection using Spatiotemporal Convolutional Networks." @default.
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• W3037967553 hasPublicationYear "2020" @default.
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