1 citations · 2 across the 4 of their papers we have counts for
6 papers
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…
QID: Efficient Query-Informed ViTs in Data-Scarce Regimes for OCR-free Visual Document Understanding
Binh M. Le, Shaoyuan Xu, Jinmiao Fu +6
In Visual Document Understanding (VDU) tasks, fine-tuning a pre-trained Vision-Language Model (VLM) with new datasets often falls short in optimizing the vision encoder to identify…
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…
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…
Quality-Agnostic Deepfake Detection with Intra-model Collaborative Learning
Binh M. Le, Simon S. Woo
Deepfake has recently raised a plethora of societal concerns over its possible security threats and dissemination of fake information. Much research on deepfake detection has been…
Towards Understanding of Deepfake Videos in the Wild
Beomsang Cho, Binh M. Le, Jiwon Kim +4
Deepfakes have become a growing concern in recent years, prompting researchers to develop benchmark datasets and detection algorithms to tackle the issue. However, existing dataset…