论文标题
检测和本地化复制移动和图像切割伪造
Detecting and Localizing Copy-Move and Image-Splicing Forgery
论文作者
论文摘要
在虚假新闻和深击世界中，有很多令人震惊的图像案例被篡改和发表在报纸上，在法庭上使用，并在社交媒体上发布出于诽谤目的。检测这些篡改的图像是一项重要的任务，我们试图解决。在本文中，我们关注的方法是检测图像是否已篡改使用深度学习和图像转换方法并比较每种方法的性能和鲁棒性。然后，我们尝试识别图像的篡改区域并预测相应的面罩。根据结果，提供了建议和方法，以实现更强大的框架来检测和识别伪造。
In the world of fake news and deepfakes, there have been an alarmingly large number of cases of images being tampered with and published in newspapers, used in court, and posted on social media for defamation purposes. Detecting these tampered images is an important task and one we try to tackle. In this paper, we focus on the methods to detect if an image has been tampered with using both Deep Learning and Image transformation methods and comparing the performances and robustness of each method. We then attempt to identify the tampered area of the image and predict the corresponding mask. Based on the results, suggestions and approaches are provided to achieve a more robust framework to detect and identify the forgeries.
