✨Training-free Detection of Generated Videos via Spatial-Temporal Likelihoods
📝 Summary:
STALL is a training-free, model-agnostic detector for generated videos. It jointly models spatial and temporal evidence from real-data statistics within a probabilistic framework. STALL consistently outperforms prior image and video-based baselines, improving reliable detection.
🔹 Publication Date: Published on Mar 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15026
• PDF: https://arxiv.org/pdf/2603.15026
• Project Page: https://omerbenhayun.github.io/stall-video/
• Github: https://github.com/OmerBenHayun/stall-video
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#Deepfakes #VideoDetection #ComputerVision #AI #DigitalForensics
📝 Summary:
STALL is a training-free, model-agnostic detector for generated videos. It jointly models spatial and temporal evidence from real-data statistics within a probabilistic framework. STALL consistently outperforms prior image and video-based baselines, improving reliable detection.
🔹 Publication Date: Published on Mar 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15026
• PDF: https://arxiv.org/pdf/2603.15026
• Project Page: https://omerbenhayun.github.io/stall-video/
• Github: https://github.com/OmerBenHayun/stall-video
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#Deepfakes #VideoDetection #ComputerVision #AI #DigitalForensics