DeepFake Detection

59 papers with code • 4 benchmarks • 12 datasets

DeepFakes involves videos, often obscene, in which a face can be swapped with someone else’s using neural networks. DeepFakes are a general public concern, thus it's important to develop methods to detect them.

Description source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Image source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Libraries

Use these libraries to find DeepFake Detection models and implementations

Most implemented papers

FaceForensics++: Learning to Detect Manipulated Facial Images

ondyari/FaceForensics 25 Jan 2019

In particular, the benchmark is based on DeepFakes, Face2Face, FaceSwap and NeuralTextures as prominent representatives for facial manipulations at random compression level and size.

The DeepFake Detection Challenge (DFDC) Dataset

polimi-ispl/icpr2020dfdc 12 Jun 2020

In addition to Deepfakes, a variety of GAN-based face swapping methods have also been published with accompanying code.

MesoNet: a Compact Facial Video Forgery Detection Network

DariusAf/MesoNet 4 Sep 2018

This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face.

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

danmohaha/celeb-deepfakeforensics CVPR 2020

AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information.

Unmasking DeepFakes with simple Features

cc-hpc-itwm/DeepFakeDetection 2 Nov 2019

In this work, we present a simple way to detect such fake face images - so-called DeepFakes.

Face X-ray for More General Face Forgery Detection

neverUseThisName/Face-X-Ray CVPR 2020

For this reason, face X-ray provides an effective way for detecting forgery generated by most existing face manipulation algorithms.

DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection

deepfakes/faceswap 1 Jan 2020

The free access to large-scale public databases, together with the fast progress of deep learning techniques, in particular Generative Adversarial Networks, have led to the generation of very realistic fake content with its corresponding implications towards society in this era of fake news.

Video Face Manipulation Detection Through Ensemble of CNNs

polimi-ispl/icpr2020dfdc 16 Apr 2020

In this paper, we tackle the problem of face manipulation detection in video sequences targeting modern facial manipulation techniques.

Combining EfficientNet and Vision Transformers for Video Deepfake Detection

davide-coccomini/Combining-EfficientNet-and-Vision-Transformersfor-Video-Deepfake-Detection 6 Jul 2021

Traditionally, Convolutional Neural Networks (CNNs) have been used to perform video deepfake detection, with the best results obtained using methods based on EfficientNet B7.

FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset

dash-lab/fakeavceleb 11 Aug 2021

We generate this dataset using the most popular deepfake generation methods.