Image Forgery Detection and Localization (and related) Papers List
Image Tampering Detection using ELA and CNN
A collection of deep learning approaches and datasets publicly available for image forgery and deepfakes detection
This system is Used detect and highlight the image (Forgery) malpractices performed on modern-day digital images.
aim of this project is to give insight into authenticity of an image using ELA and metadata analysis based weather validation
This repository was built for image tampering detection.
PixelGuard is a powerful Python-based tool designed to detect image tampering using SHA-256 hashing, metadata analysis, and pixel-level comparison. It helps verify the authenticity of images and identify unauthorized modifications, making it useful for digital forensics, cybersecurity, and content verification.
Paper code: Image tampering localization network based on multi-class attention and progressive subtraction
Image Tampering Detection WebApp made with Flask
A privacy-preserving image forgery detection framework using Federated Learning. Combines FedYogi optimization with CNN and ResNet50 to handle non-IID forensic data. Trains models collaboratively without sharing raw images, improving stability and accuracy on CASIA 1.0.
Add a description, image, and links to the image-tampering-detection topic page so that developers can more easily learn about it.
To associate your repository with the image-tampering-detection topic, visit your repo's landing page and select "manage topics."