---
author:
- |
    Andreas Rössler^1^     Davide Cozzolino^2^     Luisa Verdoliva^2^     Christian Riess^3^\
    Justus Thies^1^        Matthias Nie[ß]{}ner^1^\
    ^1^Technical University of Munich      ^2^University Federico II of Naples      ^3^University of Erlangen-Nuremberg
title: 'FaceForensics++: Learning to Detect Manipulated Facial Images '
---

Introduction
============

Related Work
============

Large-Scale Facial Forgery Database
===================================

Forgery Detection
=================

Benchmark
=========

Discussion & Conclusion
=======================

Acknowledgement
===============

We gratefully acknowledge the support of this research by the AI Foundation, a TUM-IAS Rudolf Mö[ß]{}bauer Fellowship, the ERC Starting Grant *Scan2CAD* (804724), and a Google Faculty Award. We would also like to thank Google’s Chris Bregler for help with the cloud computing. In addition, this material is based on research sponsored by the Air Force Research Laboratory and the Defense Advanced Research Projects Agency under agreement number FA8750-16-2-0204. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory and the Defense Advanced Research Projects Agency or the U.S. Government.

Appendix {#appendix .unnumbered}
========
