This work addresses the task of detecting the tampering of images in which multiple images are combined into one (image splicing). To this end the authors introduce a novel generative adversarial training technique consiting of four models that are trained simultaneously. The method is shown to perform very well on existing data sets and a novel large scale image manipulation dataset. The experiments are detailed and code and data set will be made available. Three expert reviewers initially assessed the work as 8/7/5, and the authors provided a detailed rebuttal; two reviewers acknowledge reading the rebuttal and one adjusted the score, for a final rating of 8/7/6. Remaining concerns are around clarity of writing and limited analysis studying the high effectiveness of the method in more detail. Overall, this is an important problem and the paper makes a clear contribution, both in terms of an interesting novel method and a new data set.