collaborators

7 papers

cs.CV2026

PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection

Kutub Uddin, Nusrat Tasnim, Khalid Malik

AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap between synthetic and authentic co…

cs.CV2026

Uncertainty-Aware Deepfake Detection via Multi-View Structural Learning

Muhammad Umar Farooq, Kutub Uddin, Awais Khan +1

Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution shift. This challenge is espec…

cs.CV2026

Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection

Kutub Uddin, Nusrat Tasnim, Awais Khan +2

The rapid advancement of generative AI has enabled the creation of highly realistic deepfake media, posing significant threats, including misinformation, digital identity theft, fr…

cs.CV2025

AI-Generated Image Detection: An Empirical Study and Future Research Directions

Nusrat Tasnim, Kutub Uddin, Khalid Mahmood Malik

The threats posed by AI-generated media, particularly deepfakes, are now raising significant challenges for multimedia forensics, misinformation detection, and biometric system res…

cs.SD2025

Adversarial Attacks on Audio Deepfake Detection: A Benchmark and Comparative Study

Kutub Uddin, Muhammad Umar Farooq, Awais Khan +1

The widespread use of generative AI has shown remarkable success in producing highly realistic deepfakes, posing a serious threat to various voice biometric applications, including…

cs.CV2025

A Lightweight and Interpretable Deepfakes Detection Framework

Muhammad Umar Farooq, Ali Javed, Khalid Mahmood Malik +1

The recent realistic creation and dissemination of so-called deepfakes poses a serious threat to social life, civil rest, and law. Celebrity defaming, election manipulation, and de…