3 papers
cs.CV2026
Only Whats Necessary: Pareto Optimal Data Minimization for Privacy Preserving Video Anomaly Detection
Nazia Aslam, Abhisek Ray, Thomas B. Moeslund +1
Video anomaly detection (VAD) systems are increasingly deployed in safety critical environments and require a large amount of data for accurate detection. However, such data may co…
cs.CV2026
From Pixels to Privacy: Temporally Consistent Video Anonymization via Token Pruning for Privacy Preserving Action Recognition
Nazia Aslam, Abhisek Ray, Joakim Bruslund Haurum +2
Recent advances in large-scale video models have significantly improved video understanding across domains such as surveillance, healthcare, and entertainment. However, these model…
cs.CV2025
Balancing Privacy and Action Performance: A Penalty-Driven Approach to Image Anonymization
Nazia Aslam, Kamal Nasrollahi
The rapid development of video surveillance systems for object detection, tracking, activity recognition, and anomaly detection has revolutionized our day-to-day lives while settin…