4 citations · 12 across the 7 of their papers we have counts for
7 papers
CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detection
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
The recent advancements in Generative Adversarial Networks (GANs) and the emergence of Diffusion models have significantly streamlined the production of highly realistic and widely…
Online Multimedia Verification with Computational Tools and OSINT: Russia-Ukraine Conflict Case Studies
Sohail Ahmed Khan, Jan Gunnar Furuly, Henrik Brattli Vold +2
This paper investigates the use of computational tools and Open-Source Intelligence (OSINT) techniques for verifying online multimedia content, with a specific focus on real-world…
Detecting Out-of-Context Image-Caption Pairs in News: A Counter-Intuitive Method
Eivind Moholdt, Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
The growth of misinformation and re-contextualized media in social media and news leads to an increasing need for fact-checking methods. Concurrently, the advancement in generative…
Deepfake Detection: A Comparative Analysis
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
This paper present a comprehensive comparative analysis of supervised and self-supervised models for deepfake detection. We evaluate eight supervised deep learning architectures an…
Grand Challenge On Detecting Cheapfakes
Duc-Tien Dang-Nguyen, Sohail Ahmed Khan, Cise Midoglu +3
Cheapfake is a recently coined term that encompasses non-AI ("cheap") manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media…
Hybrid Transformer Network for Deepfake Detection
Sohail Ahmed Khan, Duc-Tien Dang-Nguyen
Deepfake media is becoming widespread nowadays because of the easily available tools and mobile apps which can generate realistic looking deepfake videos/images without requiring a…