3 papers
cs.CV2025
ALFred: An Active Learning Framework for Real-world Semi-supervised Anomaly Detection with Adaptive Thresholds
Shanle Yao, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Video Anomaly Detection (VAD) can play a key role in spotting unusual activities in video footage. VAD is difficult to use in real-world settings due to the dynamic nature of human…
cs.CV2024
Evaluating the Effectiveness of Video Anomaly Detection in the Wild: Online Learning and Inference for Real-world Deployment
Shanle Yao, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Video Anomaly Detection (VAD) identifies unusual activities in video streams, a key technology with broad applications ranging from surveillance to healthcare. Tackling VAD in real…
cs.CV2023
Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community College
Shanle Yao, Babak Rahimi Ardabili, Armin Danesh Pazho +3
Smart Video surveillance systems have become important recently for ensuring public safety and security, especially in smart cities. However, applying real-time artificial intellig…