Freely available and easy-to-use audio editing tools make it straightforward
to perform audio splicing. Convincing forgeries can be created by combining
various speech samples from the same person. Detection of such splices is
important both in the public sector when considering misinf
本文提出了一种名为 Deep Matching and Validation Network（DMVN）的新型深度卷积神经网络架构，该方法可以同时定位和检测图像拼接，不依赖于手工特征，并使用原始输入图像创建深度学习表示，通过端到端优化产生概率估计和分割掩模，通过广泛的实验表明，此方法在 AUC 得分和速度方面都大大优于现有的拼接检测方法。