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Detecting Photoshopped Faces by Scripting Photoshop

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arxiv 1906.05856 v2 pith:SCBTZMTH submitted 2019-06-13 cs.CV

classification cs.CV
keywords imagephotoshopapplieddetectingfacesimagesmanipulationmanipulations
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Most malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop. We present a method for detecting one very popular Photoshop manipulation -- image warping applied to human faces -- using a model trained entirely using fake images that were automatically generated by scripting Photoshop itself. We show that our model outperforms humans at the task of recognizing manipulated images, can predict the specific location of edits, and in some cases can be used to "undo" a manipulation to reconstruct the original, unedited image. We demonstrate that the system can be successfully applied to real, artist-created image manipulations.

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Cited by 1 Pith paper

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  1. EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

    cs.CV 2026-07 conditional novelty 6.0 of 10

    EVAS localizes sparse multimodal forgeries via multi-stage audio-visual synergy and decoupled boundary-aware refinement, reporting SOTA AP and AR on LAV-DF, AV-Deepfake1M, and TVIL.

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