FAKE VIDEO DETECTION WITH CERTAINTY-BASED ATTENTION NETWORK

DeepFake synthesizes realistic fake videos that could be used maliciously such as manipulation and harassment. In order to prevent such malicious usages, detecting fake videos is immediately needed. In this paper, we propose a novel fake video detection method by adopting predictive uncertainty in detection. We devise the certainty-based attention network which guides to focus certainty-key frames in detecting fake videos. In addition, certainty-based attention is proposed for refining the features with consideration for frame-level certainty. Experiments are performed to validate the effectiveness of the proposed method by comparing the existing methods on the Celeb-DF, the latest DeepFake dataset.