Online video anomaly detection
Y Zhang, J Song, Y Jiang, H Li - Sensors, 2023 - mdpi.com
With the popularity of video surveillance technology, people are paying more and more
attention to how to detect abnormal states or events in videos in time. Therefore, real-time …
attention to how to detect abnormal states or events in videos in time. Therefore, real-time …
Weakly-supervised video anomaly detection with snippet anomalous attention
With a focus on abnormal events contained within untrimmed videos, there is increasing
interest among researchers in video anomaly detection. Among different video anomaly …
interest among researchers in video anomaly detection. Among different video anomaly …
A novel deep learning model for medical image segmentation with convolutional neural network and transformer
Z Zhang, H Wu, H Zhao, Y Shi, J Wang, H Bai… - Interdisciplinary Sciences …, 2023 - Springer
Accurate segmentation of medical images is essential for clinical decision-making, and deep
learning techniques have shown remarkable results in this area. However, existing …
learning techniques have shown remarkable results in this area. However, existing …
VGGM: Variational Graph Gaussian Mixture Model for Unsupervised Change Point Detection in Dynamic Networks
Change point detection in dynamic networks aims to detect the points of sudden change or
abnormal events within the network. It has garnered substantial interest from researchers …
abnormal events within the network. It has garnered substantial interest from researchers …
Transformer-based Spatio-Temporal Unsupervised Traffic Anomaly Detection in Aerial Videos
Anomaly detection is an area of video analysis and plays an increasing role in ensuring
safety, preventing risks, and guaranteeing quick response in intelligent surveillance …
safety, preventing risks, and guaranteeing quick response in intelligent surveillance …
Weakly-supervised video anomaly detection via temporal resolution feature learning
S Peng, Y Cai, Z Yao, M Tan - Applied Intelligence, 2023 - Springer
Weakly supervised video anomaly detection (WS-VAD) is often formulated as a multiple
instance learning (MIL) problem. Snippet-level anomaly scores can be predicted using only …
instance learning (MIL) problem. Snippet-level anomaly scores can be predicted using only …
Research and application of Transformer based anomaly detection model: A literature review
M Ma, L Han, C Zhou - arXiv preprint arXiv:2402.08975, 2024 - arxiv.org
Transformer, as one of the most advanced neural network models in Natural Language
Processing (NLP), exhibits diverse applications in the field of anomaly detection. To inspire …
Processing (NLP), exhibits diverse applications in the field of anomaly detection. To inspire …
Detecting and Quantifying Crowd-level Abnormal Behaviors in Crowd Events
L Luo, S Xie, H Yin, C Peng… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Detecting and quantifying abnormal crowd motion emerging from complex interactions of
individuals is paramount to ensure the safety of crowds. Crowd-level abnormal behaviors …
individuals is paramount to ensure the safety of crowds. Crowd-level abnormal behaviors …
Improving End-to-end Sign Language Translation with Adaptive Video Representation Enhanced Transformer
The aim of end-to-end sign language translation (SLT) is to interpret continuous sign
language (SL) video sequences into coherent natural language sentences without any …
language (SL) video sequences into coherent natural language sentences without any …
A Lightweight Video Anomaly Detection Model with Weak Supervision and Adaptive Instance Selection
Y Wang, J Zhou, J Guan - arXiv preprint arXiv:2310.05330, 2023 - arxiv.org
Video anomaly detection is to determine whether there are any abnormal events, behaviors
or objects in a given video, which enables effective and intelligent public safety …
or objects in a given video, which enables effective and intelligent public safety …