SOTAVerified

Video Anomaly Detection

Papers

Showing 151–200 of 262 papers

TitleStatusHype
Motion-Aware Feature for Improved Video Anomaly Detection—0
A Promotion Method for Generation Error Based Video Anomaly Detection—0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions—0
Multi-Contextual Predictions with Vision Transformer for Video Anomaly Detection—0
Multi-level Memory-augmented Appearance-Motion Correspondence Framework for Video Anomaly Detection—0
Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection—0
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection—0
Video Event Restoration Based on Keyframes for Video Anomaly Detection—0
Multi-scale Spatial-temporal Interaction Network for Video Anomaly Detection—0
Multi-Scale Video Anomaly Detection by Multi-Grained Spatio-Temporal Representation Learning—0
Multi-Task Learning based Video Anomaly Detection with Attention—0
Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection—0
Contrastive-Regularized U-Net for Video Anomaly Detection—0
Noise-Resistant Video Anomaly Detection via RGB Error-Guided Multiscale Predictive Coding and Dynamic Memory—0
Continuous GNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning—0
Context-aware Video Anomaly Detection in Long-Term Datasets—0
Object-centric and memory-guided normality reconstruction for video anomaly detection—0
Object Class Aware Video Anomaly Detection through Image Translation—0
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data—0
Online Anomaly Detection over Live Social Video Streaming—0
Open-Vocabulary Video Anomaly Detection—0
Patch Spatio-Temporal Relation Prediction for Video Anomaly Detection—0
Pedestrian Spatio-Temporal Information Fusion For Video Anomaly Detection—0
Configurable Spatial-Temporal Hierarchical Analysis for Flexible Video Anomaly Detection—0
Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder—0
Advancing Video Anomaly Detection: A Concise Review and a New Dataset—0
A Deep Learning Approach to Video Anomaly Detection using Convolutional Autoencoders—0
Prior Knowledge Guided Network for Video Anomaly Detection—0
Privacy-Preserving Video Anomaly Detection: A Survey—0
Privacy-Protecting Behaviours of Risk Detection in People with Dementia using Videos—0
ComplexVAD: Detecting Interaction Anomalies in Video—0
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods—0
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies—0
Clustering Driven Deep Autoencoder for Video Anomaly Detection—0
RandomSEMO: Normality Learning Of Moving Objects For Video Anomaly Detection—0
Real-world Video Anomaly Detection by Extracting Salient Features in Videos—0
Weakly Supervised Video Anomaly Detection Based on Cross-Batch Clustering Guidance—0
Bidirectional skip-frame prediction for video anomaly detection with intra-domain disparity-driven attention—0
Rethinking Metrics and Benchmarks of Video Anomaly Detection—0
Rethinking Video Anomaly Detection - A Continual Learning Approach—0
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction—0
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency—0
Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos—0
Self-Supervised Representation Learning for Visual Anomaly Detection—0
Self-Supervised Representation Learning via Neighborhood-Relational Encoding—0
Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection—0
Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement—0
A Survey on Deep Learning Techniques for Video Anomaly Detection—0
Skeletal Video Anomaly Detection using Deep Learning: Survey, Challenges and Future Directions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PoseWatch-HAUC87.23—Unverified
2MoPRLAUC84.3—Unverified
3TSGADAUC81.77—Unverified
4TrajRECAUC77.9—Unverified
5MoCoDADAUC77.6—Unverified
6COSKAD-euclideanAUC77.1—Unverified
7Multi-timescale PredictionAUC77—Unverified
8COSKAD-hyperbolicAUC75.6—Unverified
9MPED-RNNAUC75.4—Unverified
10COSKAD-radialAUC75.2—Unverified
#ModelMetricClaimedVerifiedStatus
1TrajRECAUC89.4—Unverified
2MoCoDADAUC89—Unverified
3Multi-timescale PredictionAUC88.33—Unverified
4COSKAD-euclideanAUC87.8—Unverified
5COSKAD-hyperbolicAUC87.3—Unverified
6BiPOCOAUC87—Unverified
7MPED-RNNAUC86.3—Unverified
8PredAUC86.2—Unverified
9Conv-AEAUC84.8—Unverified
10COSKAD-radialAUC82.2—Unverified
#ModelMetricClaimedVerifiedStatus
1MoCoDADAUC68.4—Unverified
2TrajRECAUC68.2—Unverified
3COSKAD-hyperbolicAUC65.5—Unverified
4COSKAD-euclideanAUC65.2—Unverified
5COSKAD-radialAUC63.4—Unverified
6MPED-RNNAUC61.2—Unverified
7GEPCAUC55.2—Unverified
8BiPOCOAUC52.3—Unverified
#ModelMetricClaimedVerifiedStatus
1VADMambaAUC91.5—Unverified
2MAMAAUC91.2—Unverified
3HF2-VADAUC91.1—Unverified
4AnyAnomalyAUC87.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PoseWatch-HAUC85.75—Unverified
2TSGADAUC80.6—Unverified
3VADMambaAUC77—Unverified
4HF2-VADAUC76.2—Unverified
#ModelMetricClaimedVerifiedStatus
1AnyAnomalyAUC74.5—Unverified
2TrajRECAUC68—Unverified
#ModelMetricClaimedVerifiedStatus
1PoseWatch-HAUC67.04—Unverified
#ModelMetricClaimedVerifiedStatus
1MULDE-object-centric-microAUC94.3—Unverified
#ModelMetricClaimedVerifiedStatus
1HF2-VADAUC0.99—Unverified
#ModelMetricClaimedVerifiedStatus
1AnyAnomalyAUC79.7—Unverified
#ModelMetricClaimedVerifiedStatus
1VADMambaAUC98.5—Unverified