29 citations · 29 across the 4 of their papers we have counts for
4 papers
Statistics-aware Audio-visual Deepfake Detector
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
In this paper, we propose an enhanced audio-visual deep detection method. Recent methods in audio-visual deepfake detection mostly assess the synchronization between audio and visu…
Targeted Augmented Data for Audio Deepfake Detection
Marcella Astrid, Enjie Ghorbel, Djamila Aouada
The availability of highly convincing audio deepfake generators highlights the need for designing robust audio deepfake detectors. Existing works often rely solely on real and fake…
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data
Marcella Astrid, Muhammad Zaigham Zaheer, Seung-Ik Lee
In order to devise an anomaly detection model using only normal training data, an autoencoder (AE) is typically trained to reconstruct the data. As a result, the AE can extract nor…
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies
Marcella Astrid, Muhammad Zaigham Zaheer, Seung-Ik Lee
Due to the rarity of anomalous events, video anomaly detection is typically approached as one-class classification (OCC) problem. Typically in OCC, an autoencoder (AE) is trained t…