19 citations · 44 across the 15 of their papers we have counts for
7 papers · 1 filter
From Frames to Events: Rethinking Evaluation in Human-Centric Video Anomaly Detection
Narges Rashvand, Shanle Yao, Armin Danesh Pazho +2
Pose-based Video Anomaly Detection (VAD) has gained significant attention for its privacy-preserving nature and robustness to environmental variations. However, traditional frame-l…
Shopformer: Transformer-Based Framework for Detecting Shoplifting via Human Pose
Narges Rashvand, Ghazal Alinezhad Noghre, Armin Danesh Pazho +2
Shoplifting remains a costly issue for the retail sector, but traditional surveillance systems, which are mostly based on human monitoring, are still largely ineffective, with only…
Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmark
Armin Danesh Pazho, Shanle Yao, Ghazal Alinezhad Noghre +3
Human-centric Video Anomaly Detection (VAD) aims to identify human behaviors that deviate from normal. At its core, human-centric VAD faces substantial challenges, such as the comp…
From Lab to Field: Real-World Evaluation of an AI-Driven Smart Video Solution to Enhance Community Safety
Shanle Yao, Babak Rahimi Ardabili, Armin Danesh Pazho +4
This article adopts and evaluates an AI-enabled Smart Video Solution (SVS) designed to enhance safety in the real world. The system integrates with existing infrastructure camera n…
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…
Ancilia: Scalable Intelligent Video Surveillance for the Artificial Intelligence of Things
Armin Danesh Pazho, Christopher Neff, Ghazal Alinezhad Noghre +4
With the advancement of vision-based artificial intelligence, the proliferation of the Internet of Things connected cameras, and the increasing societal need for rapid and equitabl…
CHAD: Charlotte Anomaly Dataset
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Babak Rahimi Ardabili +2
In recent years, we have seen a significant interest in data-driven deep learning approaches for video anomaly detection, where an algorithm must determine if specific frames of a…