activity
20242026
most citedFrom Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users

12 citations · 16 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Machine Pareidolia: Protecting Facial Image with Emotional Editing

Binh M. Le, Simon S. Woo

The proliferation of facial recognition (FR) systems has raised privacy concerns in the digital realm, as malicious uses of FR models pose a significant threat. Traditional counter…

cs.CV2025

Through the Lens: Benchmarking Deepfake Detectors Against Moiré-Induced Distortions

Razaib Tariq, Minji Heo, Simon S. Woo +1

Deepfake detection remains a pressing challenge, particularly in real-world settings where smartphone-captured media from digital screens often introduces Moiré artifacts that can…

cs.CV2025★ 12 cited

From Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users

Shahroz Tariq, Simon S. Woo, Priyanka Singh +3

The proliferation of deepfake technologies poses urgent challenges and serious risks to digital integrity, particularly within critical sectors such as forensics, journalism, and t…

cs.CV2024

Exploring the Impact of Moire Pattern on Deepfake Detectors

Razaib Tariq, Shahroz Tariq, Simon S. Woo

Deepfake detection is critical in mitigating the societal threats posed by manipulated videos. While various algorithms have been developed for this purpose, challenges arise when…

cs.CV2024

Impact of Architectural Modifications on Deep Learning Adversarial Robustness

Firuz Juraev, Mohammed Abuhamad, Simon S. Woo +2

Rapid advancements of deep learning are accelerating adoption in a wide variety of applications, including safety-critical applications such as self-driving vehicles, drones, robot…

cs.CV2024★ 1 cited

Gradient Alignment for Cross-Domain Face Anti-Spoofing

Binh M. Le, Simon S. Woo

Recent advancements in domain generalization (DG) for face anti-spoofing (FAS) have garnered considerable attention. Traditional methods have focused on designing learning objectiv…

cs.CV2024★ 3 cited

SoK: Systematization and Benchmarking of Deepfake Detectors in a Unified Framework

Binh M. Le, Jiwon Kim, Simon S. Woo +3

Deepfakes have rapidly emerged as a serious threat to society due to their ease of creation and dissemination, triggering the accelerated development of detection technologies. How…