52 citations · 99 across the 32 of their papers we have counts for
33 papers
Evidence Triangulation for Multimodal Fact-Checking in the Wild
Stefanos-Iordanis Papadopoulos, Zacharias Chrysidis, Christos Koutlis +2
The proliferation of multimedia content on social platforms has fueled multimodal misinformation, where images are used to reinforce false claims. Consequently, Multimodal Fact-Che…
Automated In-the-Wild Data Collection for Continual AI Generated Image Detection
Thanasis Pantsios, Dimitrios Karageorgiou, Christos Koutlis +3
The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existing detectors often suffer fr…
AuViRe: Audio-visual Speech Representation Reconstruction for Deepfake Temporal Localization
Christos Koutlis, Symeon Papadopoulos
With the rapid advancement of sophisticated synthetic audio-visual content, e.g., for subtle malicious manipulations, ensuring the integrity of digital media has become paramount.…
Designing and Generating Diverse, Equitable Face Image Datasets for Face Verification Tasks
Georgia Baltsou, Ioannis Sarridis, Christos Koutlis +1
Face verification is a significant component of identity authentication in various applications including online banking and secure access to personal devices. The majority of the…
VB-Mitigator: An Open-source Framework for Evaluating and Advancing Visual Bias Mitigation
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Bias in computer vision models remains a significant challenge, often resulting in unfair, unreliable, and non-generalizable AI systems. Although research into bias mitigation has…
Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters?
Despina Konstantinidou, Dimitrios Karageorgiou, Christos Koutlis +3
As generative Artificial Intelligence (AI) advances, the realism of AI generated imagery has reached a threshold capable of deceiving even vigilant human observers. Yet, while curr…
Composite Data Augmentations for Synthetic Image Detection Against Real-World Perturbations
Efthymia Amarantidou, Christos Koutlis, Symeon Papadopoulos +1
The advent of accessible Generative AI tools enables anyone to create and spread synthetic images on social media, often with the intention to mislead, thus posing a significant th…
Latent Reconstruction from Generated Data for Multimodal Misinformation Detection
Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos +1
Multimodal misinformation, such as miscaptioned images, where captions misrepresent an image's origin, context, or meaning, poses a growing challenge in the digital age. Due to the…
FaceX: Understanding Face Attribute Classifiers through Summary Model Explanations
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
EXplainable Artificial Intelligence (XAI) approaches are widely applied for identifying fairness issues in Artificial Intelligence (AI) systems. However, in the context of facial a…
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…
A CLIP-based siamese approach for meme classification
Javier Huertas-Tato, Christos Koutlis, Symeon Papadopoulos +2
Memes are an increasingly prevalent element of online discourse in social networks, especially among young audiences. They carry ideas and messages that range from humorous to hate…
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…
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…
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…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…
RED-DOT: Multimodal Fact-checking via Relevant Evidence Detection
Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos +1
Online misinformation is often multimodal in nature, i.e., it is caused by misleading associations between texts and accompanying images. To support the fact-checking process, rese…
FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning
Arjun Roy, Christos Koutlis, Symeon Papadopoulos +1
The generalisation capacity of Multi-Task Learning (MTL) suffers when unrelated tasks negatively impact each other by updating shared parameters with conflicting gradients. This is…
Towards Fair Face Verification: An In-depth Analysis of Demographic Biases
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Deep learning-based person identification and verification systems have remarkably improved in terms of accuracy in recent years; however, such systems, including widely popular cl…
MemeFier: Dual-stage Modality Fusion for Image Meme Classification
Christos Koutlis, Manos Schinas, Symeon Papadopoulos
Hate speech is a societal problem that has significantly grown through the Internet. New forms of digital content such as image memes have given rise to spread of hate using multim…
FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Bias in computer vision systems can perpetuate or even amplify discrimination against certain populations. Considering that bias is often introduced by biased visual datasets, many…
VERITE: A Robust Benchmark for Multimodal Misinformation Detection Accounting for Unimodal Bias
Stefanos-Iordanis Papadopoulos, Christos Koutlis, Symeon Papadopoulos +1
Multimedia content has become ubiquitous on social media platforms, leading to the rise of multimodal misinformation (MM) and the urgent need for effective strategies to detect and…