Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization

Understand

In this paper, we analyse the generalization ability of binary classifiers for the task of deepfake detection.

• We find that the stumbling block to their generalization is caused by the unexpected learned identity representation on images.
• Termed as the Implicit Identity Leakage, this phenomenon has been qualitatively and quantitatively verified among various DNNs.
• Furthermore, based on such understanding, we propose a simple yet effective method named the ID-unaware Deepfake Detection Model to reduce the influence of this phenomenon.