Image Forgery Detection and Localization (and related) Papers List

The aim of this project is to detect copy move forgery in image forgery detection. Based on Deep learning techniques(CNN, NN)

Official code for CAT-Net: Compression Artifact Tracing Network. Image manipulation detection and localization.

Official repository of "Deep Image Composition Meets Image Forgery"

Fusion Transformer with Object Mask Guidance for Image Forgery Analysis

Official repository of "Deep Image Restoration For Image Anti-Forensics"

Image forgery detection using CNN fusion model achieving 85% test accuracy. Features ELA preprocessing and fusion of InceptionV3, VGG16, and MobileNetV2. Ideal for digital forensics.

Ghiro docker image

Image Forgery Detection using Deep learning Graduation project

Image forgery detection using CNN and Jgeg compression

Image Forgery Detection using ELA and Deep Learning

Passport document verifications using machine learning python sklearn

Image Forgery Detection Using Passive Approach

Image forgery detection using convolutional neural networks. Group 10's final project for TU Delft's course CS4180 Deep Learning 2019.

Semester VI project

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.

Image Forgery Detection using ELA and Deep Learning

This system is Used detect and highlight the image (Forgery) malpractices performed on modern-day digital images.

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.

Image manipulation detection