UniCaCLF trains temporal instant features to separate real from forged moments relative to each sample's global context, achieving state-of-the-art temporal forgery localization on five public datasets.
Learning from yourself: A self-distillation method for fake speech detection,
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Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization
UniCaCLF trains temporal instant features to separate real from forged moments relative to each sample's global context, achieving state-of-the-art temporal forgery localization on five public datasets.