Transformer-Based Feature Compensation and Aggregation for DeepFake Detection
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DOI: 10.1109/lsp.2022.3214768
Abstract: Deepfake detection has attracted increasing attention in recent years. In this paper, we propose a transformer-based framework with feature compensation and aggregation (Trans-FCA) to extract rich forgery cues for deepfake detection. To compensate local features… read more here.
Keywords: transformer based; detection; compensation aggregation; deepfake detection ... See more keywords