Image Forgery Detection and Localization (and related) Papers List
Official code for CAT-Net: Compression Artifact Tracing Network. Image manipulation detection and localization.
Image forgery detection using convolutional neural networks. Group 10's final project for TU Delft's course CS4180 Deep Learning 2019.
Image Forgery Detection using Deep learning Graduation project
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.
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.
Benford law helps in detecting the irregularity in a set of numbers. It can be used to detect fraud in image forensics(detecting whether the image is real or fake) or it can also be used to analyze inning scores of a cricketer(predicting whether that cricketer was involved in match-fixing or not).
Reproduced Code for Image Forgery Detection papers.
Passport document verifications using machine learning python sklearn
Fusion Transformer with Object Mask Guidance for Image Forgery Analysis
Official repository of "Deep Image Composition Meets Image Forgery"
Image manipulation detection
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.
Official repository of "Deep Image Restoration For Image Anti-Forensics"
Image Forgery Detection using ELA and Deep Learning
Image Forgery Detection using ELA and Deep Learning
VerifyVision-Pro是一个全面的图像伪造篡改检测解决方案，利用深度学习（deep learning）和计算机视觉技术（cv）精确识别各类图像篡改，包括deepfake、AI生成内容、拼接操作和复制-移动篡改。基于PyTorch实现，集成了从数据处理、模型训练到部署的完整工作流程。
Image forgery detection using PRNU approach.
Add a description, image, and links to the image-forgery-detection topic page so that developers can more easily learn about it.
To associate your repository with the image-forgery-detection topic, visit your repo's landing page and select "manage topics."