Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization. (arXiv:2108.12947v2 [eess.IV] UPDATED)

Detecting and localizing image manipulation are necessary to counter
malicious use of image editing techniques. Accordingly, it is essential to
distinguish between authentic and tampered regions by analyzing intrinsic
statistics in an image. We focus on JPEG compression artifacts left during
image acquisition and editing. We propose a convolutional neural network (CNN)
that uses discrete cosine transform (DCT) coefficients, where compression
artifacts remain, to localize image manipulation. Standard CNNs cannot learn
the distribution of DCT coefficients because the convolution throws …

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