7 citations · 20 across the 12 of their papers we have counts for
12 papers
M2S2L: Mamba-based Multi-Scale Spatial-temporal Learning for Video Anomaly Detection
Yang Liu, Boan Chen, Xiaoguang Zhu +3
Video anomaly detection (VAD) is an essential task in the image processing community with prospects in video surveillance, which faces fundamental challenges in balancing detection…
Privacy-Preserving Video Anomaly Detection: A Survey
Yang Liu, Siao Liu, Xiaoguang Zhu +7
Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anomalous events that may cause harm…
End-Cloud Collaboration Framework for Advanced AI Customer Service in E-commerce
Liangyu Teng, Yang Liu, Jing Liu +1
In recent years, the e-commerce industry has seen a rapid increase in the demand for advanced AI-driven customer service solutions. Traditional cloud-based models face limitations…
Networking Systems for Video Anomaly Detection: A Tutorial and Survey
Jing Liu, Yang Liu, Jieyu Lin +7
The increasing utilization of surveillance cameras in smart cities, coupled with the surge of online video applications, has heightened concerns regarding public security and priva…
Learning Causality-inspired Representation Consistency for Video Anomaly Detection
Yang Liu, Zhaoyang Xia, Mengyang Zhao +7
Video anomaly detection is an essential yet challenging task in the multimedia community, with promising applications in smart cities and secure communities. Existing methods attem…
AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception
Dingkang Yang, Shuai Huang, Zhi Xu +12
Driver distraction has become a significant cause of severe traffic accidents over the past decade. Despite the growing development of vision-driven driver monitoring systems, the…
Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perception
Kun Yang, Dingkang Yang, Jingyu Zhang +6
Multi-agent collaborative perception as a potential application for vehicle-to-everything communication could significantly improve the perception performance of autonomous vehicle…
Enhance Multi-Scale Spatial-Temporal Coherence for Configurable Video Anomaly Detection
Kai Cheng, Xinzhe Li, Lijuan Che
The development of unsupervised Video Anomaly Detection (VAD) relies on technologies in the field of signal processing. Since the anomaly is quite ambiguous and unbounded, differen…
Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models
Yang Liu, Dingkang Yang, Yan Wang +5
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance systems, enabling the temporal or spatial identification of anomalous events within vid…
Three High-rate Beamforming Methods for Active IRS-aided Wireless Network
Feng Shu, Jing liu, Yeqing Lin +5
Due to its ability of breaking the double-fading effect experienced by passive intelligent reflecting surface (IRS), active IRS is evolving a potential technique for future 6G wire…
LGN-Net: Local-Global Normality Network for Video Anomaly Detection
Mengyang Zhao, Xinhua Zeng, Yang Liu +4
Video anomaly detection (VAD) has been intensively studied for years because of its potential applications in intelligent video systems. Existing unsupervised VAD methods tend to l…
Learning Appearance-motion Normality for Video Anomaly Detection
Yang Liu, Jing Liu, Mengyang Zhao +3
Video anomaly detection is a challenging task in the computer vision community. Most single task-based methods do not consider the independence of unique spatial and temporal patte…