论文标题
VideoForensicsHQ：检测高质量操纵的面部视频
VideoForensicsHQ: Detecting High-quality Manipulated Face Videos
论文作者
论文摘要
人们担心，可能会滥用合成高质量面部视频的新方法来以恶意的意图操纵视频。因此，研究界开发了用于检测改良的素材和为此任务组装基准数据集的方法。在本文中，我们研究了伪造探测器的性能如何取决于人眼可以看到的人工制品的存在。我们介绍了一个新的基准数据集，以进行视频伪造，并具有前所未有的质量。它使我们能够证明现有的检测技术在发现可靠地蒙上人类眼睛的假货方面存在困难。因此，我们介绍了一个新的探测器家族，该家族在检测准确性和概括方面检查了空间和时间特征的组合，并且胜过现有的方法。
There are concerns that new approaches to the synthesis of high quality face videos may be misused to manipulate videos with malicious intent. The research community therefore developed methods for the detection of modified footage and assembled benchmark datasets for this task. In this paper, we examine how the performance of forgery detectors depends on the presence of artefacts that the human eye can see. We introduce a new benchmark dataset for face video forgery detection, of unprecedented quality. It allows us to demonstrate that existing detection techniques have difficulties detecting fakes that reliably fool the human eye. We thus introduce a new family of detectors that examine combinations of spatial and temporal features and outperform existing approaches both in terms of detection accuracy and generalization.
