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Nesryne Mejri

2 accepted papers

2024

LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection

CVPR 2024poster

This paper introduces a novel approach for high-quality deepfake detection called Localized Artifact Attention Network (LAA-Net). Existing methods for high-quality deepfake detection are mainly based on a supervised binary classifier coupled with an implicit attention mechanism. As a result they do…

2023

UNTAG: Learning Generic Features for Unsupervised Type-Agnostic Deepfake Detection

ICASSP 2023accepted

This paper introduces a novel framework for unsupervised type-agnostic deepfake detection called UNTAG. Existing methods are generally trained in a supervised manner at the classification level, focusing on detecting at most two types of forgeries; thus, limiting their generalization capability acro…

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