1 citations · 1 across the 4 of their papers we have counts for
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When AUC Misleads: Polarization-Aware Evaluation of Deepfake Detectors under Domain Shift
Dat Nguyen, Cosmin Radoi, Romain Hermary +4
Recent advances in generative AI, such as diffusion models and face-swapping tools, have enabled the creation of highly realistic deepfakes, leading to real-world harms including f…
Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detection
Dat Nguyen, Marcella Astrid, Anis Kacem +2
Detecting deepfake videos is highly challenging given the complexity of characterizing spatio-temporal artifacts. Most existing methods rely on binary classifiers trained using rea…
FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detection
Dat Nguyen, Marcella Astrid, Enjie Ghorbel +1
Recently, Vision Transformers (ViTs) have achieved unprecedented effectiveness in the general domain of image classification. Nonetheless, these models remain underexplored in the…
LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection
Dat Nguyen, Nesryne Mejri, Inder Pal Singh +5
This paper introduces a novel approach for high-quality deepfake detection called Localized Artifact Attention Network (LAA-Net). Existing methods for high-quality deepfake detecti…