Author

Shen Shen

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Jul 2026

EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

EVAS, an end-to-end multimodal framework for temporal forgery localization that adopts a decoupled training paradigm with auxiliary heads to disentangle representation learning from inference objectives, enhances model generalization and stability.

Shen Shen, Quan Zhang, Dan Jiang et al. · arXiv.org · 0 citations