11 citations · 33 across the 12 of their papers we have counts for
12 papers
AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection
Yichen Jiang, Mohammed Talha Alam, Sohail Ahmed Khan +2
Detectors of AI-generated images tend to inherit the biases of the data they are trained on: models fitted to GAN imagery learn to treat GAN-specific artifacts as the very definiti…
The State-of-the-Art in Lifelog Retrieval: A Review of Progress at the ACM Lifelog Search Challenge Workshop 2022-24
Allie Tran, Werner Bailer, Duc-Tien Dang-Nguyen +8
The ACM Lifelog Search Challenge (LSC) is a venue that welcomes and compares systems that support the exploration of lifelog data, and in particular the retrieval of specific infor…
The CASTLE 2024 Dataset: Advancing the Art of Multimodal Understanding
Luca Rossetto, Werner Bailer, Duc-Tien Dang-Nguyen +11
Egocentric video has seen increased interest in recent years, as it is used in a range of areas. However, most existing datasets are limited to a single perspective. In this paper,…
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…
Practical Analyses of How Common Social Media Platforms and Photo Storage Services Handle Uploaded Images
Duc-Tien Dang-Nguyen, Vegard Velle Sjøen, Dinh-Hai Le +3
The research done in this study has delved deeply into the changes made to digital images that are uploaded to three of the major social media platforms and image storage services…
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…
ACM Multimedia Grand Challenge on Detecting Cheapfakes
Shivangi Aneja, Cise Midoglu, Duc-Tien Dang-Nguyen +5
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 med…
MMSys'21 Grand Challenge on Detecting Cheapfakes
Shivangi Aneja, Cise Midoglu, Duc-Tien Dang-Nguyen +5
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…