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Deepfake Detection via Vision Transformer by Razan Gaihre is a document available to read on EtoBox.

What is Deepfake Detection via Vision Transformer about?

This document proposes a Convolutional Vision Transformer (CViT) model to detect deepfake videos. Deepfakes use deep learning to generate hyper-realistic fake images and videos by replacing faces or manipulating facial features. Current detection methods lack generalizability across different deepfake techniques. The CViT adds a CNN to extract features to a Vision Transformer (ViT) which classifies using attention. It aims to build a generalized detector through extensive data preprocessing and training on

Author

Razan Gaihre

Language

EN