| DAC(STG-NF + Jigsaw) |
- AUC
- 87.72%
|
Divide and Conquer in Video Anomaly Detection: A Comprehensive Review and New Approach 2023-09-26 |
코드 1 |
| MULDE-object-centric-micro |
- AUC
- 86.7%
|
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection 2024-03-21 |
코드 1 |
| AI-VAD |
- AUC
- 85.94%
|
An Attribute-based Method for Video Anomaly Detection 2022-12-01 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| STG-NF |
- AUC
- 85.9%
|
Normalizing Flows for Human Pose Anomaly Detection 2022-11-20 |
코드 1 |
| AnomalyRuler |
- AUC
- 85.2%
|
Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models 2024-07-14 |
코드 1 |
| VideoPatchCore |
- AUC
- 85.1%
|
VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection 2024-09-24 |
코드 1 |
| Jigsaw-VAD |
- AUC
- 84.3%
|
Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw Puzzles 2022-07-20 |
코드 1 |
| SSMTL++v2 |
- AUC
- 83.8%
- RBDC
- 47.10
- TBDC
- 85.60
|
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection 2022-07-16 |
연결 없음 |
| SSMTL+UBnormal |
- AUC
- 83.7%
- RBDC
- 47.15
- TBDC
- 86.15
|
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection 2021-11-16 |
코드 1 |
| two-stream |
- AUC
- 83.7%
|
Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection 2022-09-07 |
코드 1 |
| SSMTL+++SSMCTB |
- AUC
- 83.6%
- RBDC
- 47.73
- TBDC
- 85.65
|
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection 2022-09-25 |
코드 1 |
| Background- Agnostic Framework+SSPCAB |
- AUC
- 83.6%
|
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection 2021-11-17 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| MoPRL |
- AUC
- 83.35
|
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection 2021-12-07 |
코드 1 |
| SSMTL++v1 |
- AUC
- 82.9%
- RBDC
- 43.2
- TBDC
- 84.1
|
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection 2022-07-16 |
연결 없음 |
| Background-Agnostic Framework |
- AUC
- 82.7%
|
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video 2020-08-27 |
코드 1 · 코드 2 |
| SSMTL |
- AUC
- 82.4%
|
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning 2020-11-15 |
코드 1 |
| MULDE-frame-centric-micro |
- AUC
- 81.3%
|
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection 2024-03-21 |
코드 1 |
| TSGAD |
- AUC
- 80.6%
|
An Exploratory Study on Human-Centric Video Anomaly Detection through Variational Autoencoders and Trajectory Prediction 2024-04-29 |
코드 1 |
| DMAD |
- AUC
- 78.8%
|
Diversity-Measurable Anomaly Detection 2023-03-09 |
코드 1 |
| Object-centric AE |
- AUC
- 78.7%
|
Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video 2018-12-11 |
코드 1 |
| STPT |
- AUC
- 77.1%
- RBDC
- 51.6
- TBDC
- 84.6
|
Spatio-temporal predictive tasks for abnormal event detection in videos 2022-10-27 |
연결 없음 |
| EVAL |
- AUC
- 76.63%
- RBDC
- 59.21
- TBDC
- 89.44
|
EVAL: Explainable Video Anomaly Localization 2022-12-15 |
연결 없음 |
| MAMA |
- AUC
- 76.5%
|
Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer 2024-02-26 |
코드 1 |
| STAN |
- AUC
- 76.2%
|
STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection 2018-04-23 |
연결 없음 |
| Multi-timescale Prediction |
- AUC
- 76.03%
|
Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection 2019-08-12 |
연결 없음 |
| ASTNet |
- AUC
- 73.6
|
Attention-based residual autoencoder for video anomaly detection 2022-05-25 |
코드 1 |
| MPED-RNN |
- AUC
- 73.40%
|
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos 2019-03-08 |
코드 1 |
| Any-Shot Sequential |
- AUC
- 71.6%
|
Any-Shot Sequential Anomaly Detection in Surveillance Videos 2020-04-05 |
연결 없음 |
| Sparse Coding Stacked RNN |
- AUC
- 68.0%
|
A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework 2017-10-01 |
코드 1 |
| PGM |
- AUC
- 61.28%
- RBDC
- 45.40
- TBDC
- 81.87
|
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified 2024-07-08 |
코드 1 |