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20232026
most citedBalancing Accuracy and Training Time in Federated Learning for Violence Detection in Surveillance Videos: A Study of Neural Network Architectures

6 citations · 6 across the 6 of their papers we have counts for

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2 papers · 1 filter

cs.CV2026

Parser-Free VLM Verification for Federated Weakly Supervised Video Anomaly Detection

Sébastien Thuau, Amira Gran, Siba Haidar +1

How can vision-language models help video anomaly detection (VAD) when surveillance data remain distributed, weakly labeled, and resource-constrained? Most weakly supervised VAD me…

cs.CV2026

Federated Binary Gating with Server-Side Vision-Language Inference for Surveillance Anomaly Classification

Côme-Alexis Puech, Sébastien Thuau, Amira Gran +3

Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to raw video. In federated learn…