deepfake-detection

Multi-modal AI-generated content detection: image, video, and audio. Benchmarks, training code (DINOv2, DINOv3, ReStraV, BreathNet), and evaluation pipeline for real vs. synthetic classification with calibration-aware metrics.

Code for Video Deepfake Detector from "MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection", paper available on IEEE Transactions on Information Forensics and Security.

Real-event-anchored benchmark for detecting AI-generated videos in real-world crisis settings.

Code and models for the paper "2D3MF: Deepfake Detection using Multi Modal Middle Fusion"

[IEEE T-BIOM] FaceXBench: Evaluating Multimodal LLMs on Face Understanding

About Advanced AI-Generated Image Detection System using EfficientNetB7 with Custom Attention Mechanism. Developed for AICS 2025 (33rd Irish Conference on Artificial Intelligence and Cognitive Science). Detects deepfakes from GANs, Diffusion Models, and other generative AI.