SpecSem-Net integrates Fourier-based spectral filtering with semantic-guided gated merging to detect AI-generated videos, reporting 87.25% accuracy on a new benchmark of five commercial generators and 95.59% on public datasets.
Video swin transformer
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
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An SNN-based detector combining multi-channel pseudo-event residuals with frozen semantic features reaches 93.14% mean accuracy on unseen generators under the Pika-trained GenVideo protocol.
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SpecSem-Net: Integrating Spectral and Semantic Features for Robust AI-generated Video Detection
SpecSem-Net integrates Fourier-based spectral filtering with semantic-guided gated merging to detect AI-generated videos, reporting 87.25% accuracy on a new benchmark of five commercial generators and 95.59% on public datasets.
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Detecting AI-Generated Videos with Spiking Neural Networks
An SNN-based detector combining multi-channel pseudo-event residuals with frozen semantic features reaches 93.14% mean accuracy on unseen generators under the Pika-trained GenVideo protocol.