Weakly-supervised Video Anomaly Detection
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Benchmarks
UBnormal
Most implemented
Real-world Anomaly Detection in Surveillance Videos
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection
Papers
CADE: Continual Weakly-supervised Video Anomaly Detection with Ensembles
Video anomaly detection (VAD) has long been studied as a crucial problem in public security and crime prevention. In recent years, weakly-supervised VAD (WVAD) have attracted considerable attention due to their easy anno…
Weakly-supervised Video Anomaly DetectionContinual LearningRefineVAD: Semantic-Guided Feature Recalibration for Weakly Supervised Video Anomaly Detection
Weakly-Supervised Video Anomaly Detection aims to identify anomalous events using only video-level labels, balancing annotation efficiency with practical applicability. However, existing methods often oversimplify the an…
Weakly-supervised Video Anomaly DetectionLearning to Tell Apart: Weakly Supervised Video Anomaly Detection via Disentangled Semantic Alignment
Recent advancements in weakly-supervised video anomaly detection have achieved remarkable performance by applying the multiple instance learning paradigm based on multimodal foundation models such as CLIP to highlight an…
Weakly-supervised Video Anomaly DetectionMultiple Instance LearningContrastive LearningMixture of Experts Guided by Gaussian Splatters Matters: A new Approach to Weakly-Supervised Video Anomaly Detection
Video Anomaly Detection (VAD) is a challenging task due to the variability of anomalous events and the limited availability of labeled data. Under the Weakly-Supervised VAD (WSVAD) paradigm, only video-level labels are p…
Weakly-supervised Video Anomaly DetectionGV-VAD : Exploring Video Generation for Weakly-Supervised Video Anomaly Detection
Video anomaly detection (VAD) plays a critical role in public safety applications such as intelligent surveillance. However, the rarity, unpredictability, and high annotation cost of real-world anomalies make it difficul…
Weakly-supervised Video Anomaly DetectionVideo GenerationDual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
Federated weakly supervised video anomaly detection represents a significant advancement in privacy-preserving collaborative learning, enabling distributed clients to train anomaly detectors using only video-level annota…
Anomaly DetectionAnomaly Detection In Surveillance VideosEdge-computingFederated Learning+5