collaborators

22 papers

cs.CV2026

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…

cs.CV2026

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)…

cs.AI2026

Intelligent CCTV for Urban Design: AI-Based Analysis of Soft Infrastructure at Intersections

Vinit Katariya, Seungjin Kim, Curtis Craig +2

Artificial intelligence (AI) and computer vision are transforming transportation data collection. This study introduces an AI-enabled analytics framework leveraging existing CCTV i…

cs.CV2026

Anatomy-Aware Unsupervised Detection and Localization of Retinal Abnormalities in Optical Coherence Tomography

Tania Haghighi, Sina Gholami, Hamed Tabkhi +1

Reliable automated analysis of Optical Coherence Tomography (OCT) imaging is crucial for diagnosing retinal disorders but faces a critical barrier: the need for expensive, labor-in…

cs.CY2026

Community-Led AI Integration for Wildfire Risk Assessment: A Participatory AI Literacy and Explainability Integration (PALEI) Framework in Los Angeles, CA

Sanaz Sadat Hosseini, Mona Azarbayjani, Mohammad Pourhomayoun +1

Climate-driven wildfires are intensifying, particularly in urban regions such as Southern California. Yet, traditional fire risk communication tools often fail to gain public trust…

cs.CV2026

EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

Seungjin Kim, Reza Jafarpourmarzouni, Christopher Neff +2

Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end latency. We present EdgeVTP,…