Anomaly Detection on CUHK Avenue

Metric: TBDC (higher is better)

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#	Model↕	TBDC▼	Augmentations	Paper	Date↕	Code
1	HF2VAD+SSPCAB	89.28	No	Self-Supervised Predictive Convolutional Attenti...	2021-11-17	Code
2	EVAL	87.56	No	EVAL: Explainable Video Anomaly Localization	2022-12-15	-
3	SSMTL++v2	85.2	No	-	-	-
4	SSMTL++v1	82.1	No	SSMTL++: Revisiting Self-Supervised Multi-Task L...	2022-07-16	-
5	Siamese Net	78.6	No	Learning a distance function with a Siamese netw...	2020-01-24	-
6	PGM	72.09	No	Bounding Boxes and Probabilistic Graphical Model...	2024-07-08	Code
7	PGM	72.09	No	Bounding Boxes and Probabilistic Graphical Model...	2024-07-08	Code
8	Background-Agnostic Framework	66.85	Yes	A Background-Agnostic Framework with Adversarial...	2020-08-27	Code
9	SD-MAE	66.58	No	Self-Distilled Masked Auto-Encoders are Efficien...	2023-06-21	Code
10	Background-Agnostic Framework+SSMCTB	65.12	No	Self-Supervised Masked Convolutional Transformer...	2022-09-25	Code
11	SSMTL+UBnormal	61.38	Yes	UBnormal: New Benchmark for Supervised Open-Set ...	2021-11-16	Code
12	SSMTL	58.3	No	Anomaly Detection in Video via Self-Supervised a...	2020-11-15	Code
13	Future Frame Prediction	56.01	No	Future Frame Prediction for Anomaly Detection --...	2017-12-28	Code
14	Object-centric AE	27.01	No	Object-centric Auto-encoders and Dummy Anomalies...	2018-12-11	Code

#1HF2VAD+SSPCABSOTA
89.28
TBDC· 2021-11-17
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection Code
#2EVAL
87.56
TBDC· 2022-12-15
EVAL: Explainable Video Anomaly Localization
#3SSMTL++v2
85.2
TBDC
No paper
#4SSMTL++v1
82.1
TBDC· 2022-07-16
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
#5Siamese NetSOTA
78.6
TBDC· 2020-01-24
Learning a distance function with a Siamese network to localize anomalies in videos
#6PGM
72.09
TBDC· 2024-07-08
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified Code
#7PGM
72.09
TBDC· 2024-07-08
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified Code
#8Background-Agnostic Framework
66.85
TBDC· Augmentations· 2020-08-27
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video Code
#9SD-MAE
66.58
TBDC· 2023-06-21
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors Code
#10Background-Agnostic Framework+SSMCTB
65.12
TBDC· 2022-09-25
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection Code
#11SSMTL+UBnormal
61.38
TBDC· Augmentations· 2021-11-16
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection Code
#12SSMTL
58.3
TBDC· 2020-11-15
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning Code
#13Future Frame PredictionSOTA
56.01
TBDC· 2017-12-28
Future Frame Prediction for Anomaly Detection -- A New Baseline Code
#14Object-centric AE
27.01
TBDC· 2018-12-11
Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video Code