  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 https://github.com/oidelima/Deepfake-Detection.
