Detection-of-face-Manipulated-videos

This is the implementation code for Detection of Manipulated Facial Images using Faceforensics++ data.

For detailed documentation please refer following medium link.

https://medium.com/analytics-vidhya/detection-of-face-manipulated-videos-using-deep-learning-6bca870f3a6a?source=friends_link&sk=46e2f2beb6415cba6850cb66bc0bcd43

Problem Definition:

As there is a lot of active research going on image/video generation and manipulation, that helps to evolve many new ways to manipulate the original sources at the same time this leads to a loss of trust in digital content, but it might even cause further harm by spreading false information and the creation of fake news.

Objective

We need to build a model such that it should recognize whether the given video(or image sequence) is fake or real.

Data Background

The Faceforensics++ data was collected by Visual Computing Group (http://niessnerlab.org/ (http://niessnerlab.org/)) , one can obtain this data on accepting their terms and conditions.

In short

1. Total 1000 videos (videos are like news readers reading news) are downloaded from youtube.
2. Manipulated vidoes are generated by using 3 automated state-of-the-art face manipulation methods (viz., DeepFakes, FaceSwap, Face2Face) that are applied to these 1,000 pristine videos.
3. Gathered images from these both pritine videos(real) and manipulated videos(fake)

To get more understanding please visit https://arxiv.org/abs/1901.08971

and to download and extract the data please visit https://github.com/ondyari/FaceForensics (https://github.com/ondyari/FaceForensics)

Files in this Repository

1. Data_Analysis_Extraction.ipynb ----> this file contains understanding and extracting and preprocessing the data
2. modeling.ipynb -----> All modeling part was included in this file
3. final.ipynb -----> Total pipline for performing video classification was included in this file