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 …
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 …
Ted-spad: Temporal distinctiveness for self-supervised privacy-preservation for video anomaly detection
Video anomaly detection (VAD) without human monitoring is a complex computer vision task
that can have a positive impact on society if implemented successfully. While recent …
that can have a positive impact on society if implemented successfully. While recent …
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 …
Batchnorm-based weakly supervised video anomaly detection
In weakly supervised video anomaly detection (WVAD), where only video-level labels
indicating the presence or absence of abnormal events are available, the primary challenge …
indicating the presence or absence of abnormal events are available, the primary challenge …
Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detection
Weakly supervised video anomaly detection (WSVAD) is a challenging task. Generating fine-
grained pseudo-labels based on weak-label and then self-training a classifier is currently a …
grained pseudo-labels based on weak-label and then self-training a classifier is currently a …
Video anomaly detection and explanation via large language models
H Lv, Q Sun - arxiv preprint arxiv:2401.05702, 2024 - arxiv.org
Video Anomaly Detection (VAD) aims to localize abnormal events on the timeline of long-
range surveillance videos. Anomaly-scoring-based methods have been prevailing for years …
range surveillance videos. Anomaly-scoring-based methods have been prevailing for years …
Prompt-Enhanced Multiple Instance Learning for Weakly Supervised Video Anomaly Detection
Abstract Weakly-supervised Video Anomaly Detection (wVAD) aims to detect frame-level
anomalies using only video-level labels in training. Due to the limitation of coarse-grained …
anomalies using only video-level labels in training. Due to the limitation of coarse-grained …
Open-World Semantic Segmentation Including Class Similarity
Interpreting camera data is key for autonomously acting systems such as autonomous
vehicles. Vision systems that operate in real-world environments must be able to understand …
vehicles. Vision systems that operate in real-world environments must be able to understand …