Cross-domain video anomaly detection without target domain adaptation
Most cross-domain unsupervised Video Anomaly Detection (VAD) works assume that at
least few task-relevant target domain training data are available for adaptation from the …
least few task-relevant target domain training data are available for adaptation from the …
Overlooked video classification in weakly supervised video anomaly detection
Current weakly supervised video anomaly detection algorithms mostly use multiple instance
learning (MIL) or their varieties. Almost all recent approaches focus on how to select the …
learning (MIL) or their varieties. Almost all recent approaches focus on how to select the …
End-to-end learning for weakly supervised video anomaly detection using Absorbing Markov Chain
We propose a principled deep neural network framework with Absorbing Markov Chain
(AMC) for weakly supervised anomaly detection in surveillance videos. Our model consists …
(AMC) for weakly supervised anomaly detection in surveillance videos. Our model consists …
Anomaly crossing: New horizons for video anomaly detection as cross-domain few-shot learning
Video anomaly detection aims to identify abnormal events that occurred in videos. Since
anomalous events are relatively rare, it is not feasible to collect a balanced dataset and train …
anomalous events are relatively rare, it is not feasible to collect a balanced dataset and train …
Dual-Modality Deep Feature-based Anomaly Detection for Video Surveillance
PL Bhatt, D Shah, C Silver, W Zhang… - 2023 IEEE Canadian …, 2023 - ieeexplore.ieee.org
Detecting anomalies in videos is not only crucial but also an intriguing task in surveillance
systems. It is a sequential modeling problem in nature that requires careful selection of …
systems. It is a sequential modeling problem in nature that requires careful selection of …