Change Detection On Levir
Métriques
F1
IoU
OA
Prcision
Recall
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | F1 | IoU | OA | Prcision | Recall | Paper Title | Repository |
|---|---|---|---|---|---|---|---|
| BiFA | 83.96 | 72.35 | 98.69 | 83.85 | 84.06 | BiFA: Remote Sensing Image Change Detection With Bitemporal Feature Alignment | |
| HANet | 77.56 | 63.34 | 98.22 | 79.70 | 75.53 | HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images | |
| HCGMNet | 82.37 | 70.03 | 98.57 | 82.81 | 81.94 | HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection | |
| ChangeMamba | 88.39 | 79.20 | 99.06 | 89.24 | 87.57 | ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model | |
| CDMamba | 83.01 | 70.95 | 98.65 | 85.11 | 81.00 | CDMamba: Remote Sensing Image Change Detection with Mamba | |
| CGNet | 83.68 | 71.94 | 98.63 | 81.46 | 86.02 | Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery | |
| C2FNet | 79.15 | 65.50 | 98.26 | 77.19 | 81.22 | C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images |
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