是真的还是假的?一种检测调质图像的实用方法

Ching-yu Kao, Hongjia Wan, Karla Markert, Konstantin Böttinger
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引用次数: 0

摘要

篡改图像已经成为几乎每个人都能掌握的技术,包括假新闻、法庭上的假证据或伪造文件。主要原因是因为这些编辑工具,比如Photoshop,使用简单,这是我们急需解决的问题。因此,帮助找出被操纵图像的自动工具对于打击虚假信息活动至关重要。在此,我们提出并评估了一种基于神经网络的方法。它可以检测图像是否被人为修改(分类),并进一步指出伪造部分(分割)。与大多数基线方法相比,我们提出的方法具有更好的性能。最后,我们的方法不仅对JPEG格式有效,也适用于其他格式。
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Real or Fake? A Practical Method for Detecting Tempered Images
Tempering images has become technology that almost everyone can complete, including fake news, fake evidence presented in court, or forged documents. The main reason is because these editing tools, such as Photoshop, is simple to use, which is an urgent issue we need to solve. Hence, automatic tools helping to find manipulated images apart is critical for fighting misinformation campaigns. Here we propose and evaluate a neural network-based method. It can detect whether images have been artificially modified (classification), and further indicate the forged parts (segmentation). Our proposed method has better performance than most baseline methods. Last but not least, our method is not only effective on JPEG format, but can also be used on other formats.
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