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Can We Leave Deepfake Data Behind in Training Deepfake Detector? Jikang Cheng

Neural Information Processing Systems

The generalization ability of deepfake detectors is vital for their applications in real-world scenarios. One effective solution to enhance this ability is to train the models with manually-blended data, which we termed "blendfake", encouraging models to