Implementation of the paper A Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer

Java program to perform error level analysis on images

phoenix is a small command line image forensics tool

Assignments for the CS763 : Computer Vision Course at IIT Bombay

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

Distinguishing Between Natural and Computer-Generated Images Using Convolutional Neural Networks in Keras.

💡 Detecting processing history of images by using Deep Learning

Image tamper detection based on demosaicing artifacts

Tampering detection related sources

Implementation of paper "Exposing Digital Forgeries by Detecting Inconsistencies in Lighting"

Computer Graphics vs Real Photographic Images : A Deep-learning approach

The assignments and projects on Digital Image Processing

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

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

Image forgery detection using PRNU approach.

2016JFS, Source camera identification with content adaptive guided filter

MTA2020: A noise-based image splicing localization method for the case that the source images are with distinct ISO settings

IWDW2020: ISO Setting Estimation Based on Convolutional Neural Network

Electronic Imaging 2021

Reproduced Code for Image Forgery Detection papers.