Just Dance: detection of human body reenactment fake videos

IF 2.4 4区 计算机科学
Omran Alamayreh, Carmelo Fascella, Sara Mandelli, Benedetta Tondi, Paolo Bestagini, Mauro Barni
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引用次数: 0

Abstract

In the last few years, research on the detection of AI-generated videos has focused exclusively on detecting facial manipulations known as deepfakes. Much less attention has been paid to the detection of artificial non-facial fake videos. In this paper, we address a new forensic task, namely, the detection of fake videos of human body reenactment. To this purpose, we consider videos generated by the “Everybody Dance Now” framework. To accomplish our task, we have constructed and released a novel dataset of fake videos of this kind, referred to as FakeDance dataset. Additionally, we propose two forgery detectors to study the detectability of FakeDance kind of videos. The first one exploits spatial–temporal clues of a given video by means of hand-crafted descriptors, whereas the second detector is an end-to-end detector based on Convolutional Neural Networks (CNNs) trained on purpose. Both detectors have their peculiarities and strengths, working well in different operative scenarios. We believe that our proposed dataset together with the two detectors will contribute to the research on the detection of non-facial fake videos generated by means of AI.

Abstract Image

Just Dance:检测人体再现假视频
在过去几年中,有关人工智能生成视频检测的研究主要集中在检测被称为深度伪造的面部操纵上。而对人工非面部伪造视频的检测则关注较少。在本文中,我们将讨论一项新的取证任务,即检测人体再现的虚假视频。为此,我们考虑了由 "Everybody Dance Now "框架生成的视频。为了完成任务,我们构建并发布了一个新颖的此类伪造视频数据集,称为 FakeDance 数据集。此外,我们还提出了两种伪造检测器来研究 FakeDance 类视频的可检测性。第一个检测器通过手工创建的描述符来利用给定视频的时空线索,而第二个检测器则是基于专门训练的卷积神经网络(CNN)的端到端检测器。这两种检测器各有特点和优势,在不同的工作场景下都能发挥良好的作用。我们相信,我们提出的数据集和这两种检测器将有助于通过人工智能手段检测非人脸伪造视频的研究。
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来源期刊
Eurasip Journal on Image and Video Processing
Eurasip Journal on Image and Video Processing Engineering-Electrical and Electronic Engineering
CiteScore
7.10
自引率
0.00%
发文量
23
审稿时长
6.8 months
期刊介绍: EURASIP Journal on Image and Video Processing is intended for researchers from both academia and industry, who are active in the multidisciplinary field of image and video processing. The scope of the journal covers all theoretical and practical aspects of the domain, from basic research to development of application.
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