Detecting Photoshopped Faces by Scripting Photoshop
Abstract
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 artist-created image manipulations.
Cite
Text
Wang et al. "Detecting Photoshopped Faces by Scripting Photoshop." Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019. doi:10.1109/ICCV.2019.01017Markdown
[Wang et al. "Detecting Photoshopped Faces by Scripting Photoshop." Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019.](https://mlanthology.org/iccv/2019/wang2019iccv-detecting/) doi:10.1109/ICCV.2019.01017BibTeX
@inproceedings{wang2019iccv-detecting,
title = {{Detecting Photoshopped Faces by Scripting Photoshop}},
author = {Wang, Sheng-Yu and Wang, Oliver and Owens, Andrew and Zhang, Richard and Efros, Alexei A.},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision},
year = {2019},
doi = {10.1109/ICCV.2019.01017},
url = {https://mlanthology.org/iccv/2019/wang2019iccv-detecting/}
}