2 citations · 9 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…