19 citations · 19 across the 3 of their papers we have counts for
4 papers
SAVe: Self-Supervised Audio-visual Deepfake Detection Exploiting Visual Artifacts and Audio-visual Misalignment
Sahibzada Adil Shahzad, Ammarah Hashmi, Junichi Yamagishi +5
Multimodal deepfakes can exhibit subtle visual artifacts and cross-modal inconsistencies, which remain challenging to detect, especially when detectors are trained primarily on cur…
Understanding Audiovisual Deepfake Detection: Techniques, Challenges, Human Factors and Perceptual Insights
Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2
Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be…
Unmasking Illusions: Understanding Human Perception of Audiovisual Deepfakes
Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2
The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the in…
AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection
Ammarah Hashmi, Sahibzada Adil Shahzad, Chia-Wen Lin +2
The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intellige…