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Anomaly Detection On Chuk Avenue

Metrics

AUC
RBDC
TBDC

Results

Performance results of various models on this benchmark

Paper Title
MULDE-object-centric-micro94.3%--MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection
AMSRC93.8%--A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency
SSMTL++v193.7%40.982.1SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
AI-VAD93.7%--An Attribute-based Method for Video Anomaly Detection
Background-Agnostic Framework+SSMCTB93.2%66.0465.12Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection
SSMTL+UBnormal93.0%61.1061.38UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
Background- Agnostic Framework+SSPCAB92.9%65.99-Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
VideoPatchCore92.8%--VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection
DMAD92.8%--Diversity-Measurable Anomaly Detection
PGM92.72%60.1872.09Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified
Background-Agnostic Framework92.3%65.0566.85A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video
SSMTL++v291.6%47.885.2-
SSMTL91.5%57.0058.30Anomaly Detection in Video via Self-Supervised and Multi-Task Learning
SD-MAE91.3%46.7766.58Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors
MAMA91.2%--Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer
VALD-GAN91.03--VALD-GAN: video anomaly detection using latent discriminator augmented GAN
Two-stream90.8%--Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection
AnomalyRuler89.7%--Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models
Cloze Test89.6%--Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events
Narrowed Normality Clusters88.9%--Detecting abnormal events in video using Narrowed Normality Clusters
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Anomaly Detection On Chuk Avenue | SOTA | HyperAI