| MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection | ✓ Link | 94.3% | | | | MULDE-object-centric-micro | 2024-03-21 |
| A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency | | 93.8% | | | | AMSRC | 2022-04-08 |
| SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection | | 93.7% | 40.9 | 82.1 | 20 | SSMTL++v1 | 2022-07-16 |
| An Attribute-based Method for Video Anomaly Detection | ✓ Link | 93.7% | | | | AI-VAD | 2022-12-01 |
| Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection | ✓ Link | 93.2% | 66.04 | 65.12 | 24 | Background-Agnostic Framework+SSMCTB | 2022-09-25 |
| UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection | ✓ Link | 93.0% | 61.10 | 61.38 | | SSMTL+UBnormal | 2021-11-16 |
| Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection | ✓ Link | 92.9% | 65.99 | | 24 | Background- Agnostic Framework+SSPCAB | 2021-11-17 |
| Diversity-Measurable Anomaly Detection | ✓ Link | 92.8% | | | | DMAD | 2023-03-09 |
| VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection | ✓ Link | 92.8% | | | | VideoPatchCore | 2024-09-24 |
| Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified | ✓ Link | 92.72% | 60.18 | 72.09 | | PGM | 2024-07-08 |
| A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video | ✓ Link | 92.3% | 65.05 | 66.85 | 25 | Background-Agnostic Framework | 2020-08-27 |
| []() | | 91.6% | 47.8 | 85.2 | 19 | SSMTL++v2 | |
| Anomaly Detection in Video via Self-Supervised and Multi-Task Learning | ✓ Link | 91.5% | 57.00 | 58.30 | 51 | SSMTL | 2020-11-15 |
| Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors | ✓ Link | 91.3% | 46.77 | 66.58 | 1670 | SD-MAE | 2023-06-21 |
| Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer | ✓ Link | 91.2% | | | | MAMA | 2024-02-26 |
| VALD-GAN: video anomaly detection using latent discriminator augmented GAN | | 91.03 | | | | VALD-GAN | 2023-10-18 |
| Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly Detection | ✓ Link | 90.8% | | | | Two-stream | 2022-09-07 |
| Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models | ✓ Link | 89.7% | | | | AnomalyRuler | 2024-07-14 |
| Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events | ✓ Link | 89.6% | | | 5 | Cloze Test | 2020-08-27 |
| Detecting abnormal events in video using Narrowed Normality Clusters | | 88.9% | | | | Narrowed Normality Clusters | 2018-01-12 |
| Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation | ✓ Link | 88.3% | | | 1480 | AKD-VAD | 2022-11-28 |
| Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video | ✓ Link | 87.4% | 15.77 | 27.01 | | Object-centric AE | 2018-12-11 |
| Learning a distance function with a Siamese network to localize anomalies in videos | | 87.2% | 41.20 | 78.60 | | Siamese Net | 2020-01-24 |
| Learning Not to Reconstruct Anomalies | ✓ Link | 87.1% | | | | Learning not to reconstruct | 2021-10-19 |
| Anomaly Detection in Video Sequence with Appearance-Motion Correspondence | ✓ Link | 86.9% | | | | Appearance-Motion Correspondence | 2019-08-17 |
| Attention-based residual autoencoder for video anomaly detection | ✓ Link | 86.7% | | | | ASTNet | 2022-05-25 |
| Any-Shot Sequential Anomaly Detection in Surveillance Videos | | 86.4% | | | | Any-Shot Sequential | 2020-04-05 |
| EVAL: Explainable Video Anomaly Localization | | 86.02% | 68.2 | 87.56 | | EVAL | 2022-12-15 |
| STemGAN: spatio-temporal generative adversarial network for video anomaly detection | | 86.0 | | | | STemGAN | 2023-09-22 |
| FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation | ✓ Link | 85.3% | | | 195 | FastAno | 2021-06-16 |
| Future Frame Prediction for Anomaly Detection -- A New Baseline | ✓ Link | 85.1% | 19.59 | 56.01 | 25 | Future Frame Prediction | 2017-12-28 |
| Diversity-Measurable Anomaly Detection | ✓ Link | 84.3% | | | | ConvVQ | 2023-03-09 |
| A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework | ✓ Link | 81.7% | | | | Sparse Coding Stacked RNN | 2017-10-01 |
| Unmasking the abnormal events in video | | 80.6% | | | | Unmasking | 2017-05-23 |
| Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection | ✓ Link | | | 89.28 | | HF2VAD+SSPCAB | 2021-11-17 |