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FaceForensics++: Learning to Detect Manipulated Facial Images

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Overview

FaceForensics++ is a forensics dataset consisting of 1000 original video sequences that have been manipulated with three automated face manipulation methods: Deepfakes, Face2Face and FaceSwap. The data has been sourced from 977 youtube videos and all videos contain a trackable mostly frontal face without occlusions which enables automated tampering methods to generate realistic forgeries. As we provide binary masks the data can be used for image and video classification as well as segmentation. In addition, we provide 1000 Deepfakes models to generate and augment new data.

For more information, please consult our paper.

Access

If you would like to download the FaceForensics++ dataset, please fill out an agreement to the FaceForensics Terms of Use and send it to us at [email protected].

If you have not received a response within a week, it is likely that your email is bouncing - please check this before sending repeat requests.

Once, you obtain the download link, please head to the download section. You can also find details about the generation of the dataset there.

Original FaceForensics

You can view the original FaceForensics github here. Any request will also contain the download link to the original version of our dataset.

Citation

If you use the FaceForensics++ data or code please cite:

@article{roessler2019faceforensics++,
	author = {Andreas R\"ossler and Davide Cozzolino and Luisa Verdoliva and Christian Riess and Justus Thies and Matthias Nie{\ss}ner},
	title = {FaceForensics++: Learning to Detect Manipulated Facial Images},
	journal={arXiv},
	year={2019}
}

Help

If you have any questions, please contact us at [email protected].

Video

Please view our youtube video here.

Changelog

25.01.2019: Release of FaceForensics++

License

The data is released under the FaceForensics Terms of Use, and the code is released under the MIT license.

Copyright (c) 2019

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