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Zhanhe Lei

2 accepted papers

2026

Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection

ICML 2026poster

With the evolution of generative models, deepfakes have achieved near-perfect semantic realism, leaving forensic traces only in subtle structural anomalies. However, existing single-view paradigms often fail to generalize, as dominant semantic features overwhelm subtle artifact cues within entangled…

Cited by 0SourceScholar
2026

Tutor-Student Reinforcement Learning: A Dynamic Curriculum for Robust Deepfake Detection

CVPR 2026

Standard supervised training for deepfake detection treats all samples with uniform importance, which can be suboptimal for learning robust and generalizable features. In this work, we propose a novel Tutor-Student Reinforcement Learning (TSRL) framework to dynamically optimize the training curricul

Cited by 0SourcecodeScholar