Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …
systems, enabling the temporal or spatial identification of anomalous events within videos …
[HTML][HTML] Self-training: A survey
Self-training methods have gained significant attention in recent years due to their
effectiveness in leveraging small labeled datasets and large unlabeled observations for …
effectiveness in leveraging small labeled datasets and large unlabeled observations for …
Vadclip: Adapting vision-language models for weakly supervised video anomaly detection
The recent contrastive language-image pre-training (CLIP) model has shown great success
in a wide range of image-level tasks, revealing remarkable ability for learning powerful …
in a wide range of image-level tasks, revealing remarkable ability for learning powerful …
Learning prompt-enhanced context features for weakly-supervised video anomaly detection
Weakly supervised video anomaly detection aims to locate abnormal activities in untrimmed
videos without the need for frame-level supervision. Prior work has utilized graph …
videos without the need for frame-level supervision. Prior work has utilized graph …
Open-vocabulary video anomaly detection
Current video anomaly detection (VAD) approaches with weak supervisions are inherently
limited to a closed-set setting and may struggle in open-world applications where there can …
limited to a closed-set setting and may struggle in open-world applications where there can …
Deep learning for video anomaly detection: A review
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the
normality in videos. As a long-standing task in the field of computer vision, VAD has …
normality in videos. As a long-standing task in the field of computer vision, VAD has …
Anomaly heterogeneity learning for open-set supervised anomaly detection
Open-set supervised anomaly detection (OSAD)-a recently emerging anomaly detection
area-aims at utilizing a few samples of anomaly classes seen during training to detect …
area-aims at utilizing a few samples of anomaly classes seen during training to detect …
Weakly supervised video anomaly detection and localization with spatio-temporal prompts
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-
level anomalous event detection with only coarse video-level annotations available. Existing …
level anomalous event detection with only coarse video-level annotations available. Existing …
Uncovering What Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly
Video anomaly understanding (VAU) aims to automatically comprehend unusual
occurrences in videos thereby enabling various applications such as traffic surveillance and …
occurrences in videos thereby enabling various applications such as traffic surveillance and …
Semantic-driven dual consistency learning for weakly supervised video anomaly detection
Video anomaly detection presents a significant challenge in computer vision, with the aim of
distinguishing various anomaly events from numerous normal ones. Weakly supervised …
distinguishing various anomaly events from numerous normal ones. Weakly supervised …