Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization

Detecting and localizing image manipulation are necessary to counter malicious use of editing techniques. Accordingly, it is essential distinguish between authentic tampered regions by analyzing intrinsic statistics in an image. We focus on JPEG compression artifacts left during acquisition editing. propose a convolutional neural network that uses discrete cosine transform (DCT) coefficients, where remain, localize manipulation. Standard CNNs cannot learn the distribution DCT coefficients because convolution throws away spatial coordinates, which for coefficients. illustrate how design train can Furthermore, we introduce Compression Artifact Tracing Network jointly artifacts. It significantly outperforms traditional deep network-based methods detecting regions.