Recently, a video of famous politicians and superstars giving certain speeches surfaced online causing severe political and commercial problems. The video, although it seemed authentic, was fake. Therefore, in this study, using 37,936 videos sampled from the deep fake detection challenge (DFDC), we developed an efficient and highly accurate deepfake detection system using EfficientNet with dynamic images. Dynamic image transforms video sequences into one frame instance by conserving spatiotemporal information. The experimental results and comparative analysis indicate that EfficientNet with dynamic image exhibits higher performance than EfficientNet. We also found that dynamic images generated by 20 frames have a higher fake-face detection accuracy than simple images.
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