3 citations · 9 across the 25 of their papers we have counts for
9 papers · 2 filters
MAVias: Mitigate any Visual Bias
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Mitigating biases in computer vision models is an essential step towards the trustworthiness of artificial intelligence models. Existing bias mitigation methods focus on a small se…
DiMoDif: Discourse Modality-information Differentiation for Audio-visual Deepfake Detection and Localization
Christos Koutlis, Symeon Papadopoulos
Deepfake technology has rapidly advanced and poses significant threats to information integrity and trust in online multimedia. While significant progress has been made in detectin…
BAdd: Bias Mitigation through Bias Addition
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Computer vision (CV) datasets often exhibit biases that are perpetuated by deep learning models. While recent efforts aim to mitigate these biases and foster fair representations,…
Similarity over Factuality: Are we making progress on multimodal out-of-context misinformation detection?
Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos +1
Out-of-context (OOC) misinformation poses a significant challenge in multimodal fact-checking, where images are paired with texts that misrepresent their original context to suppor…
TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping
Despina Konstantinidou, Christos Koutlis, Symeon Papadopoulos
Generative AI technologies produce increasingly realistic imagery, which, despite its potential for creative applications, can also be misused to produce misleading and harmful con…
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…
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…
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…
Leveraging Representations from Intermediate Encoder-blocks for Synthetic Image Detection
Christos Koutlis, Symeon Papadopoulos
The recently developed and publicly available synthetic image generation methods and services make it possible to create extremely realistic imagery on demand, raising great risks…