Anomaly Detection On Chuk Avenue
评估指标
AUC
RBDC
TBDC
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | AUC | RBDC | TBDC |
|---|---|---|---|
| ubnormal-new-benchmark-for-supervised-open | 93.0% | 61.10 | 61.38 |
| a-revisit-of-sparse-coding-based-anomaly | 81.7% | - | - |
| attention-based-residual-autoencoder-for | 86.7% | - | - |
| detecting-abnormal-events-in-video-using | 88.9% | - | - |
| anomaly-detection-in-video-sequence-with | 86.9% | - | - |
| self-supervised-predictive-convolutional | - | - | 89.28 |
| diversity-measurable-anomaly-detection | 84.3% | - | - |
| self-supervised-predictive-convolutional | 92.9% | 65.99 | - |
| learning-a-distance-function-with-a-siamese | 87.2% | 41.20 | 78.60 |
| cloze-test-helps-effective-video-anomaly | 89.6% | - | - |
| future-frame-prediction-for-anomaly-detection | 85.1% | 19.59 | 56.01 |
| vald-gan-video-anomaly-detection-using-latent | 91.03 | - | - |
| 模型 13 | 91.6% | 47.8 | 85.2 |
| fastano-fast-anomaly-detection-via-spatio | 85.3% | - | - |
| learning-not-to-reconstruct-anomalies | 87.1% | - | - |
| mulde-multiscale-log-density-estimation-via | 94.3% | - | - |
| making-anomalies-more-anomalous-video-anomaly | 91.2% | - | - |
| videopatchcore-an-effective-method-to | 92.8% | - | - |
| bounding-boxes-and-probabilistic-graphical | 92.72% | 60.18 | 72.09 |
| a-video-anomaly-detection-framework-based-on | 93.8% | - | - |
| ssmtl-revisiting-self-supervised-multi-task | 93.7% | 40.9 | 82.1 |
| self-supervised-masked-convolutional | 93.2% | 66.04 | 65.12 |
| a-scene-agnostic-framework-with-adversarial | 92.3% | 65.05 | 66.85 |
| eval-explainable-video-anomaly-localization | 86.02% | 68.2 | 87.56 |
| any-shot-sequential-anomaly-detection-in | 86.4% | - | - |
| follow-the-rules-reasoning-for-video-anomaly | 89.7% | - | - |
| unmasking-the-abnormal-events-in-video | 80.6% | - | - |
| anomaly-detection-in-video-via-self | 91.5% | 57.00 | 58.30 |
| lightning-fast-video-anomaly-detection-via | 88.3% | - | - |
| self-distilled-masked-auto-encoders-are | 91.3% | 46.77 | 66.58 |
| diversity-measurable-anomaly-detection | 92.8% | - | - |
| object-centric-auto-encoders-and-dummy | 87.4% | 15.77 | 27.01 |
| context-recovery-and-knowledge-retrieval-a | 90.8% | - | - |
| attribute-based-representations-for-accurate | 93.7% | - | - |
| stemgan-spatio-temporal-generative | 86.0 | - | - |