3 papers
cs.CV2026
Only Train Once: Uncertainty-Aware One-Class Learning for Face Authenticity Detection
Qingchao Jiang, Zhenxuan Hou, Zhiying Zhu +3
The rapid evolution of generative paradigms has enabled the creation of highly realistic imagery, which escalating the risks of identity fraud and the dissemination of disinformati…
cs.CV2026
Evidence-based Decision Modeling for Synthetic Face Detection with Uncertainty-driven Active Learning
Qingchao Jiang, Zhenxuan Hou, Zhiying Zhu +3
With the rapid development of deep generative models, forged facial images are massively exploited for illegal activities. Although existing synthetic face detection methods have a…
cs.CV2025
Model Discrepancy Learning: Synthetic Faces Detection Based on Multi-Reconstruction
Qingchao Jiang, Zhishuo Xu, Zhiying Zhu +3
Advances in image generation enable hyper-realistic synthetic faces but also pose risks, thus making synthetic face detection crucial. Previous research focuses on the general diff…