most citedMINTIME: Multi-Identity Size-Invariant Video Deepfake Detection

4 citations · 7 across the 4 of their papers we have counts for

collaborators

16 papers

cs.CL202413 cited

Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checking

Zacharias Chrysidis, Stefanos-Iordanis Papadopoulos, Symeon Papadopoulos +1

Automated fact-checking (AFC) is garnering increasing attention by researchers aiming to help fact-checkers combat the increasing spread of misinformation online. While many existi…

cs.CV20241 cited

Towards Quantitative Evaluation of Explainable AI Methods for Deepfake Detection

Konstantinos Tsigos, Evlampios Apostolidis, Spyridon Baxevanakis +2

In this paper we propose a new framework for evaluating the performance of explanation methods on the decisions of a deepfake detector. This framework assesses the ability of an ex…

cs.CV2024

SIDBench: A Python Framework for Reliably Assessing Synthetic Image Detection Methods

Manos Schinas, Symeon Papadopoulos

The generative AI technology offers an increasing variety of tools for generating entirely synthetic images that are increasingly indistinguishable from real ones. Unlike methods t…

cs.CV2024

SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes

Georgia Baltsou, Ioannis Sarridis, Christos Koutlis +1

AI systems rely on extensive training on large datasets to address various tasks. However, image-based systems, particularly those used for demographic attribute prediction, face s…

cs.CV2024

Fusion Transformer with Object Mask Guidance for Image Forgery Analysis

Dimitrios Karageorgiou, Giorgos Kordopatis-Zilos, Symeon Papadopoulos

In this work, we introduce OMG-Fuser, a fusion transformer-based network designed to extract information from various forensic signals to enable robust image forgery detection and…

cs.CV2024

Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure

Alaa Elobaid, Nathan Ramoly, Lara Younes +3

Biometric Verification (BV) systems often exhibit accuracy disparities across different demographic groups, leading to biases in BV applications. Assessing and quantifying these bi…