Concept drift challenge in multimedia anomaly detection: A case study with facial datasets
Anomaly detection in multimedia datasets is a widely studied area. Yet, the concept drift
challenge in data has been ignored or poorly handled by the majority of the anomaly …
challenge in data has been ignored or poorly handled by the majority of the anomaly …
Situational anomaly detection in multimedia data under concept drift
P Kumari - Proceedings of the 29th ACM International conference …, 2021 - dl.acm.org
Anomaly detection has been a very challenging and active area of research for decades,
particularly for video surveillance. However, most of the works detect predefined anomaly …
particularly for video surveillance. However, most of the works detect predefined anomaly …
Fine-tuning the Robust Temporal Feature Magnitude model for enhancing the accuracy of anomaly detection
C Charupalli, K Seshadri - 2022 IEEE 5th International …, 2022 - ieeexplore.ieee.org
Surveillance videos can capture a variety of realistic events and also anomalies. Due to an
increase in the crime rate in public areas, surveillance cameras are adopted in a very large …
increase in the crime rate in public areas, surveillance cameras are adopted in a very large …
Multimedia datasets for anomaly detection: a review
Multimedia anomaly datasets play a crucial role in automated surveillance. They have a
wide range of applications expanding from outlier objects/situation detection to the detection …
wide range of applications expanding from outlier objects/situation detection to the detection …
Mir_mad: An efficient and on-line approach for anomaly detection in dynamic data stream
Anomaly detection in a dynamic data stream is a challenging task. The endless bound and
high arriving rate of data prohibits anomaly detection models to store all observations in …
high arriving rate of data prohibits anomaly detection models to store all observations in …
A semantic-enhanced method based on deep SVDD for pixel-wise anomaly detection
Detecting the anomalous information in multimedia is valuable to many computer vision
applications. Recently, many pixel-wise methods modeling by deep learning model have …
applications. Recently, many pixel-wise methods modeling by deep learning model have …
Weakly supervised anomaly detection with multi-level contextual modeling
M Liu, X Li, Y Liu, Y Han - Multimedia Systems, 2023 - Springer
Due to the low frequency of abnormal behaviors in the real world and the complexity of the
definition of abnormal behaviors, anomaly detection in the surveillance video is very …
definition of abnormal behaviors, anomaly detection in the surveillance video is very …
Ensemble anomaly score for video anomaly detection using denoise diffusion model and motion filters
Video anomaly detection is a crucial task that aims to differentiate between normal and
abnormal events. The current mainstream approach involves constructing an anomaly score …
abnormal events. The current mainstream approach involves constructing an anomaly score …
Semantic Features Extraction for Anomaly Detection from Real-World Videos*
MH Tran, TH Tran - 2023 RIVF International Conference on …, 2023 - ieeexplore.ieee.org
Video-based anomaly detection opens up numerous practical applications such as video
surveillance and healthcare. Despite having been studied for an extended period, this …
surveillance and healthcare. Despite having been studied for an extended period, this …
State-Transition-Aware Anomaly Detection Under Concept Drifts
Detecting temporal abnormal patterns over streaming data is challenging due to volatile
data properties and the lack of real-time labels. The abnormal patterns are usually hidden in …
data properties and the lack of real-time labels. The abnormal patterns are usually hidden in …