基于改进变压器模型的深度造假检测技术

Zhengyi Ma, Qiming Yu, Run Xue, Yan Li, Haibo Liu, Haining Li, Peilong Lu
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引用次数: 0

摘要

Deepfake开源技术将人工智能换脸的门槛降低到非常低的水平,一键换脸成为可能。“虚假信息”的成本大大降低,使得一些深度造假的图片和视频可以在社交网络上传播,社交网络可以爆发式传播。然而,在防御层中,deepfake几乎没有标准化和自动化的检测工具。没有这样的工具。因此,无论是对个人还是平台来说,打击虚假和虚假信息的时间窗口很短,但难度很大。本文以Transformer模型为基础,对模型进行改进,优化模型结构,使模型能够提取视频的深度特征,构建更加准确高效的深度检测方法。
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Deepfake detection technique based on improved transformer model
Deepfake open source technology has lowered the threshold for AI face swapping to a very low level, making it possible to swap faces with one click. The cost of "disinformation" is greatly reduced, so that some deeply faked pictures and videos can be spread on social networks The social network can spread explosively. However, in the defense layer, there are almost no standardized and automated detection tools for deepfake. There is no such tool. Therefore, whether for individuals or platforms, the time window for fighting fake and disinformation is very short, but it is very difficult. In this paper, we use the Transformer model as a base, improve the model and optimize the structure of the model, so that the model can extract the depth features of the video and build a more accurate and efficient deepfake inspection method.
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