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Qinglang Guo

2 accepted papers

2025

From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes

NeurIPS 2025poster

Detecting deepfakes has been an increasingly important topic, especially given the rapid development of AI generation techniques. In this paper, we ask: How can we build a universal detection framework that is effective for most facial deepfakes? One significant challenge is the wide variety of deep…

Cited by 0SourceScholar
2025

Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

ICASSP 2025accepted

The widespread adoption of face recognition has raised privacy concerns regarding the collection and use of facial data. To address this, researchers have explored "unlearnable examples" by adding imperceptible perturbations during model training to prevent the model from learning target features. H…

Cited by 0SourceScholar