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SOTA
異常検出
Anomaly Detection On Ucsd Ped2
Anomaly Detection On Ucsd Ped2
評価指標
AUC
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
AUC
Paper Title
Repository
Two-stream
97.1%
Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection
Background-Agnostic
98.7%
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video
STPT
98.9%
Spatio-temporal predictive tasks for abnormal event detection in videos
-
DMAD
99.7%
Diversity-Measurable Anomaly Detection
SD-MAE
95.4%
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors
MAMA
98.2%
Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer
VALD-GAN
97.74
VALD-GAN: video anomaly detection using latent discriminator augmented GAN
-
ASTNet
97.4%
Attention-based residual autoencoder for video anomaly detection
FastAno
96.3%
FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation
STemGAN
97.5
STemGAN: spatio-temporal generative adversarial network for video anomaly detection
-
AnomalyRuler
97.9%
Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models
MULDE-object-centric-micro
99.7%
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection
ConvVQ
90.2%
Diversity-Measurable Anomaly Detection
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