Deep learning has been successfully appertained to solve various complex problems in the area of big data analytics to computer vision. A deep learning-powered application recently emerged is Deep Fake. It helps to create fake images and videos that human cannot distinguish them from the real ones and are recent off-shelf manipulation technique that allows swapping two identities in a single video. Technology is a controversial technology with many wide-reaching issues impacting society. So, to counter this emerging problem, we introduce a dataset of 140k real and fake faces which contain 70k real faces from the Flickr dataset collected by Nvidia, as well as 70k fake faces sampled from 1 million fake faces generated by style GAN. We will train our model in the dataset so that our model can identify real or fake faces.
@article{arxiv.2109.05397,
title = {Challenges and Solutions in DeepFakes},
author = {Jatin Sharma and Sahil Sharma},
journal= {arXiv preprint arXiv:2109.05397},
year = {2021}
}
Comments
Paper has a lot of mistakes and is not good enough according to the technical standards a research paper should have