论文标题
使用卷积神经网络检测锻造的面部视频
Detecting Forged Facial Videos using convolutional neural network
论文作者
论文摘要
在本文中，我们建议在在线视频中检测面孔的锻造视频。为了促进此检测，我们建议使用较小的卷积神经网络（CNN），以进行数据驱动的伪造视频检测方法。为了验证我们的方法，我们调查了FaceForensics公共数据集，详细介绍了基于框架和基于视频的结果。所提出的方法显示出优于最新现状。我们还进行了消融研究，分析了批处理大小，过滤器数量以及网络层数对检测锻造视频的准确性的影响。
In this paper, we propose to detect forged videos, of faces, in online videos. To facilitate this detection, we propose to use smaller (fewer parameters to learn) convolutional neural networks (CNN), for a data-driven approach to forged video detection. To validate our approach, we investigate the FaceForensics public dataset detailing both frame-based and video-based results. The proposed method is shown to outperform current state of the art. We also perform an ablation study, analyzing the impact of batch size, number of filters, and number of network layers on the accuracy of detecting forged videos.
