Identifying Human Edited Images using a CNN

Lee, Jordan, Lin, Willy, Ntalis, Konstantinos, Shah, Anirudh, Tung, William, Wulff, Maxwell

arXiv.org Artificial Intelligence 

Most non-professional photo manipulations are not made using propriety software like Adobe Photoshop, which is expensive and complicated to use for the average consumer selfie-taker or meme-maker. Instead, these individuals opt for user friendly mobile applications like FaceTune and Pixlr to make human face edits and alterations. Unfortunately, there is no existing dataset to train a model to classify these type of manipulations. In this paper, we present a generative model that approximates the distribution of human face edits and a method for detecting Facetune and Pixlr manipulations to human faces.

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