16 citations · 20 across the 10 of their papers we have counts for
11 papers
VQ-VAD: Vector-quantized Motion Representation Learning for Human-centric Video Anomaly Detection
Narges Rashvand, Ghazal Alinezhad Noghre, Shanle Yao +2
Video Anomaly Detection (VAD) is inherently challenging due to the scarcity of anomalies and the large visual variability in surveillance footage, including changes in lighting, vi…
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…
From Offline to Periodic Adaptation for Pose-Based Shoplifting Detection in Real-world Retail Security
Shanle Yao, Narges Rashvand, Armin Danesh Pazho +1
Shoplifting is a growing operational and economic challenge for retailers, with incidents rising and losses increasing despite extensive video surveillance. Continuous human monito…
Are Multimodal LLMs Ready for Surveillance? A Reality Check on Zero-Shot Anomaly Detection in the Wild
Shanle Yao, Armin Danesh Pazho, Narges Rashvand +1
Multimodal large language models (MLLMs) have demonstrated impressive general competence in video understanding, yet their reliability for real-world Video Anomaly Detection (VAD)…
Distributed learning for automatic modulation recognition in bandwidth-limited networks
Narges Rashvand, Kenneth Witham, Gabriel Maldonado +4
Automatic Modulation Recognition (AMR) is critical in identifying various modulation types in wireless communication systems. Recent advancements in deep learning have facilitated…
Adversarially-Refined VQ-GAN with Dense Motion Tokenization for Spatio-Temporal Heatmaps
Gabriel Maldonado, Narges Rashvand, Armin Danesh Pazho +3
Continuous human motion understanding remains a core challenge in computer vision due to its high dimensionality and inherent redundancy. Efficient compression and representation a…
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…
Real-Time Bus Departure Prediction Using Neural Networks for Smart IoT Public Bus Transit
Narges Rashvand, Sanaz Sadat Hosseini, Mona Azarbayjani +1
Bus transit plays a vital role in urban public transportation but often struggles to provide accurate and reliable departure times. This leads to delays, passenger dissatisfaction,…
Exploring Pose-Based Anomaly Detection for Retail Security: A Real-World Shoplifting Dataset and Benchmark
Narges Rashvand, Ghazal Alinezhad Noghre, Armin Danesh Pazho +2
Shoplifting poses a significant challenge for retailers, resulting in billions of dollars in annual losses. Traditional security measures often fall short, highlighting the need fo…
Enhancing Automatic Modulation Recognition for IoT Applications Using Transformers
Narges Rashvand, Kenneth Witham, Gabriel Maldonado +4
Automatic modulation recognition (AMR) is vital for accurately identifying modulation types within incoming signals, a critical task for optimizing operations within edge devices i…
Real-Time Bus Arrival Prediction: A Deep Learning Approach for Enhanced Urban Mobility
Narges Rashvand, Sanaz Sadat Hosseini, Mona Azarbayjani +1
In urban settings, bus transit stands as a significant mode of public transportation, yet faces hurdles in delivering accurate and reliable arrival times. This discrepancy often cu…