3 papers
cs.CV2025
Federated Learning for Video Violence Detection: Complementary Roles of Lightweight CNNs and Vision-Language Models for Energy-Efficient Use
Sébastien Thuau, Siba Haidar, Rachid Chelouah
Deep learning-based video surveillance increasingly demands privacy-preserving architectures with low computational and environmental overhead. Federated learning preserves privacy…
cs.CV2025
Frugal Federated Learning for Violence Detection: A Comparison of LoRA-Tuned VLMs and Personalized CNNs
Sébastien Thuau, Siba Haidar, Ayush Bajracharya +1
We examine frugal federated learning approaches to violence detection by comparing two complementary strategies: (i) zero-shot and federated fine-tuning of vision-language models (…
cs.CV2025
Exploring Personalized Federated Learning Architectures for Violence Detection in Surveillance Videos
Mohammad Kassir, Siba Haidar, Antoun Yaacoub
The challenge of detecting violent incidents in urban surveillance systems is compounded by the voluminous and diverse nature of video data. This paper presents a targeted approach…