Towards deepfake detection that actually works

Code for Video Deepfake Detection model from "Combining EfficientNet and Vision Transformers for Video Deepfake Detection" presented at ICIAP 2021.

Determine whether a given video sequence has been manipulated or synthetically generated

Deepfakes Video classification via CNN, LSTM, C3D and triplets [IWBF'20]

Unofficial Implementation: Learning Self-Consistency for Deepfake Detection

This repository contains our POC for a website which can easily check videos for manipulated areas. It was part of the Hackathon for Good in the Hague, 2019.

Deepfake faces detection from forged videos where used explainable AI for models' robustness as well as cost sensitive methods for mitigating dataset imbalance problem

This project was completed as part of the Deep Learning course (GLO-4030) at Laval University. Its goal is to detect deepfake videos using deep learning techniques on the FaceForensics dataset. We were able to achieve deepfake detection by using the EfficientNet model.

Reproduction/refactoring of the FaceForensics++ classification process.

This project is based on the paper Representative Forgery Mining for Deep Fake Detection.

Replication code for the paper 'Towards DeepFake video forensics based on facial textural disparities in multi-color channels'

A Deepfake Detection Project using EfficientNetV2 and FaceForensics++ with Gradio as UI