Image Forgery Detection and Localization (and related) Papers List
AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics, WMF@CVPR2023
This GitHub provides different DeepFakes Detectors using facial regions and considering three different state-of-the-art fake detection systems.
This repository contains the official implementation (PyTorch) of "Multimodal Forgery Detection Using Ensemble Learning" proposed in APSIPA Paper 2022.
Deep learning system achieving 95.36% accuracy in media forgery detection using hybrid ResNet50+ViT architecture. Optimized for 20% training data efficiency with PyTorch, OpenCV, and Flask-based inference pipeline.
A deep learning-based web application for deepfake video detection, powered by the fine-tuned XceptionNet (Extreme Inception) model. The system allows users to upload videos for deepfake detection, processes them through the trained model, and provides results via a clean Django-based web interface.
This project implements the algorithm proposed in the paper: "A Novel Hybrid DCT and DWT Based Robust Watermarking Algorithm for Color Images" by Ahmed Khaleel Abdulrahman and Serkan Ozturk.
A modular PyTorch-based research lab for deepfake detection. Includes implementations and experiments with autoencoders, classifiers, contrastive learning, and generative-model–based detection techniques. Designed for benchmarking, reproducibility, and rapid exploration of new architectures.
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