Research Article
Integrated Multiscale Appearance Features and Motion Information Prediction Network for Anomaly Detection
Table 2
Frame-level AUC performance of different methods on UCSD dataset.
| Methods | AUC (%) | UCSD Ped1 | UCSD Ped2 |
| MDT [34] | 81.8 | 82.9 | Motion energy model [38] | 75 | 81 | Conv-AE [7] | 81.0 | 90.0 | ConvLSTM [8] | 89.9 | 87.4 | ConvLSTM-AE [9] | 75.5 | 88.1 | MGFC-AAE [10] | 85 | 91.6 | Unmasking [36] | 68.4 | 82.2 | AnomalyNet [37] | 83.5 | 94.9 | Baseline [15] | 83.1 | 95.4 | Proposed method | 84.4 | 96.3 |
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