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cs.CV2025

Detecting Text Manipulation in Images using Vision Language Models

Vidit Vidit, Pavel Korshunov, Amir Mohammadi +3

Recent works have shown the effectiveness of Large Vision Language Models (VLMs or LVLMs) in image manipulation detection. However, text manipulation detection is largely missing i…

cs.CV2025

FantasyID: A dataset for detecting digital manipulations of ID-documents

Pavel Korshunov, Amir Mohammadi, Vidit Vidit +2

Advancements in image generation led to the availability of easy-to-use tools for malicious actors to create forged images. These tools pose a serious threat to the widespread Know…

cs.CV2025

Investigation of Accuracy and Bias in Face Recognition Trained with Synthetic Data

Pavel Korshunov, Ketan Kotwal, Christophe Ecabert +3

Synthetic data has emerged as a promising alternative for training face recognition (FR) models, offering advantages in scalability, privacy compliance, and potential for bias miti…

cs.CV2024

Score Normalization for Demographic Fairness in Face Recognition

Yu Linghu, Tiago de Freitas Pereira, Christophe Ecabert +2

Fair biometric algorithms have similar verification performance across different demographic groups given a single decision threshold. Unfortunately, for state-of-the-art face reco…

cs.CV2024

SDFR: Synthetic Data for Face Recognition Competition

Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25

Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…