Hyper-realistic face image generation and manipulation have givenrise to numerous unethical social issues, e.g., invasion of privacy,threat of security, and malicious political maneuvering, which re-sulted in the development of recent deepfake detection methodswith the rising demands of deepfake forensics. Proposed deepfakedetection methods to date have shown remarkable detection perfor-mance and robustness. However, none of the suggested deepfakedetection methods assessed the performance of deepfakes withthe facemask during the pandemic crisis after the outbreak of theCovid-19. In this paper, we thoroughly evaluate the performance ofstate-of-the-art deepfake detection models on the deepfakes withthe facemask. Also, we propose two approaches to enhance themasked deepfakes detection:face-patchandface-crop. The experi-mental evaluations on both methods are assessed through the base-line deepfake detection models on the various deepfake datasets.Our extensive experiments show that, among the two methods,face-cropperforms better than theface-patch, and could be a trainmethod for deepfake detection models to detect fake faces withfacemask in real world.
翻译：超现实的面部图像生成和操纵已经暴露出许多不道德的社会问题,例如侵犯隐私、威胁安全和恶意政治操纵,随着深假法证的需求不断增长,这些在开发最近深假探测方法的过程中又重新沉没。迄今为止,拟议的深假探测方法已经显示出惊人的探测穿孔和坚固度。然而,所建议的深假探测方法都没有评估在Covid-19爆发后爆发的大流行病危机期间深假面部图像的性能。在本文件中,我们彻底评价了以面部镜为深度的深假发现模型的性能。我们还提出了两种方法,以加强面部的深假面部发现和坚固度。两种方法的外观评估都通过各种深假假死数据集的底线深底底底底底底底底部探测模型进行评估。我们进行的广泛实验表明,在两种方法中,面部的胸形形状比脸部检测假脸部模型要好得多。我们建议用两种方法来提高面部深底底底底底底底底底底底的检测模型,并用假底底底底底底底底底底底底底的底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底底
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