论文标题
使用Comprint的图像伪造检测的训练数据改进
Training Data Improvement for Image Forgery Detection using Comprint
论文作者
论文摘要
当被操纵的图像被用来传播虚假信息时，对全球消费者的威胁。因此，组合通过利用JPEG压缩指纹实现伪造检测。本文评估了培训集对构成性能的影响。最有趣的是，我们发现在训练过程中包括与低质量因子压缩的图像不会对准确性产生重大影响，而结合重新压缩则可以提高鲁棒性。因此，消费者可以在其智能手机上使用构造来验证图像的真实性。
Manipulated images are a threat to consumers worldwide, when they are used to spread disinformation. Therefore, Comprint enables forgery detection by utilizing JPEG-compression fingerprints. This paper evaluates the impact of the training set on Comprint's performance. Most interestingly, we found that including images compressed with low quality factors during training does not have a significant effect on the accuracy, whereas incorporating recompression boosts the robustness. As such, consumers can use Comprint on their smartphones to verify the authenticity of images.
