most citedADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images

9 citations · 18 across the 3 of their papers we have counts for

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cs.CV2025

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…

cs.CV20241 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.CV20231 cited

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…

cs.CV20214 cited

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images

Binh M. Le, Simon S. Woo

The rapid progression of Generative Adversarial Networks (GANs) has raised a concern of their misuse for malicious purposes, especially in creating fake face images. Although many…

cs.CV20219 cited

ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images

Binh M. Le, Simon S. Woo

Despite significant advancements of deep learning-based forgery detectors for distinguishing manipulated deepfake images, most detection approaches suffer from moderate to signific…