forgery-detection

[CVPR'19, ICLR'20] A Python toolbox for modeling and optimization of photo acquisition & distribution pipelines (camera ISP, compression, forensics, manipulation detection)

Copy-move image forgery detection library.

Groundtruth images of tampering dataset CASIA 2.0

Unofficial implementation of paper 'Face X-ray for More General Face Forgery Detection'. (updating...)

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

A collection of deep learning approaches and datasets publicly available for image forgery and deepfakes detection

Groundtruth images of tampering dataset CASIA 1.0

AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection (NeurIPS 2020)

Copy-Move forgery database with similar but Genuine objects. ICIP2016 paper

Detection of copy-move forgery in an image with CMDF methods. (SIFT, SURF, AKAZE, RANSAC)

🖼️ 🕵️ Forgery Detection on Images

image fraud detection(copy-move forgery)

This is the one of solution implemented for image forgery localization using deep learning techniques and architectures such as UNET, VGG

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

auto-encoder-based forgery detection tool for mammogram images

The assignments and projects on Digital Image Processing

Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"

A deep convolutional neural network for the detection as well as localization of the area of manipulation in forged images, bearing forgeries of simple as well as complex nature. Further along, the trained model is interfaced with a web application for users to interact with the model in a simple and effective manner, and finally, we also develo…

Implementing Copy Move Forgery Detection using DCT or SVD transformations. Also, a clear explanation is provided in the READme section

An algorithm that is completely robust to Intensity/ Brightness varied copy move forgery is proposed in this algorithm.