  In the current era, image manipulation is becoming increasingly easier,
yielding more natural looking images, owing to the modern tools in image
processing and computer vision techniques. The task of the segregation of
forged images has become very challenging. To tackle such problems, publicly
available datasets are insufficient. In this paper, we propose to create a
synthetic forged dataset using deep semantic image inpainting algorithm.
Furthermore, we use an unsupervised domain adaptation network to detect
copy-move forgery in images. Our approach can be helpful in those cases, where
the classification of data is unavailable.
