Anomaly Detection On Lost And Found
Métriques
AP
FPR
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AP | FPR | Paper Title | Repository |
|---|---|---|---|---|
| SynBoost | 70.43 | 4.89 | Pixel-wise Anomaly Detection in Complex Driving Scenes | |
| Mask2Anomaly | 86.59 | 5.75 | Unmasking Anomalies in Road-Scene Segmentation | |
| PEBAL | 78.29 | 0.81 | Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes | |
| SML | 25.89 | 44.48 | Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation |
0 of 4 row(s) selected.