Image Forgery Detection using Deep Learning, implemented in PyTorch.
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Updated
Nov 22, 2022 - Python
Image Forgery Detection using Deep Learning, implemented in PyTorch.
A collection of deep learning approaches and datasets publicly available for image forgery and deepfakes detection
AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics, WMF@CVPR2023
IFAKE is an application for detecting image and video forgery, designed to help users verify the authenticity of digital media. This repository also contains the AI model and dataset that we developed for image tampering detection, providing an effective solution for detecting image and video manipulations.
Official repository of "Deep Image Composition Meets Image Forgery"
aim of this project is to give insight into authenticity of an image using ELA and metadata analysis based weather validation
This project focuses on detecting a specific form of image forgery known as a copy-move attack, in which a portion of an image is copied and pasted elsewhere.
Forged Image To Original Image Generation
Image Forgery Detection Using Passive Approach
DeepLabV3+ based network for fake faces detection
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