Towards deepfake detection that actually works
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.
A state-of-the-art, open-source deepfake detection system built with PyTorch and EfficientNet-B0, featuring a user-friendly web interface for real-time image and video analysis.
This repo is an enhanced toolkit with some updated methods processing original FaceForensics++ dataset.
Reproduction/refactoring of the FaceForensics++ classification process.
A Deepfake Detection Project using EfficientNetV2 and FaceForensics++ with Gradio as UI
Replication code for the paper 'Towards DeepFake video forensics based on facial textural disparities in multi-color channels'
This project is based on the paper Representative Forgery Mining for Deep Fake Detection.
Deepfake detection on FaceForensics++ using ResNet50, Xception(+SE), and Swin(+SE) with face crops vs full frames, frame sampling, aggregation, and Grad-CAM.
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