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SOTA
Change Detection
Change Detection On Levir Cd
Change Detection On Levir Cd
Metrics
F1
F1-score
IoU
Overall Accuracy
Precision
Recall
Results
Performance results of various models on this benchmark
Columns
Model Name
F1
F1-score
IoU
Overall Accuracy
Precision
Recall
Paper Title
MAE+MTP(ViT-L+RVSA)
92.67
-
-
-
-
-
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
IMP+MTP(InternImage-XL)
92.54
-
-
-
-
-
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
CLAFA-LWGANet L2
92.42
92.42
85.90
-
93.25
-
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
Changer (Ex, ResNeSt101)
92.33
-
85.76
-
-
-
Changer: Feature Interaction is What You Need for Change Detection
LSKNet
92.27
92.27
85.65
-
93.34
91.23
LSKNet: A Foundation Lightweight Backbone for Remote Sensing
SRC-Net
92.24
92.24
85.60
-
-
-
SRC-Net: Bi-Temporal Spatial Relationship Concerned Network for Change Detection
MAE+MTP(ViT-B+RVSA)
92.22
-
-
-
-
-
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Changer (Ex, ResNeSt50)
92.19
-
85.51
-
-
-
Changer: Feature Interaction is What You Need for Change Detection
TTP
92.1
-
85.6
99.2
93.0
91.7
Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection
CGNet
92.01
92.01
85.21
99.20
93.15
90.90
Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
ChangeCLIP
92.01
-
85.20
99.20
93.40
90.67
ChangeCLIP: Remote sensing change detection with multimodal vision-language representation learning
P2V-CD
91.94
-
-
-
-
-
Transition Is a Process: Pair-to-Video Change Detection Networks for Very High Resolution Remote Sensing Images
C2FNet
91.83
99.18
93.69
90.04
84.89
91.40
C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
HCGMNet
91.77
91.77
84.79
99.18
92.96
90.61
HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
Changer (Ex, ResNet-18)
91.77
-
84.80
-
-
-
Changer: Feature Interaction is What You Need for Change Detection
ChangeStar(BiSup)
91.25
-
83.92
-
-
-
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery
DDPM-CD
90.91
-
-
99.09
-
-
DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
BiFA
90.69
-
82.96
99.06
91.52
89.86
BiFA: Remote Sensing Image Change Detection With Bitemporal Feature Alignment
CDMaskFormer
90.66
-
82.92
99.06
92.01
89.35
Rethinking Remote Sensing Change Detection With A Mask View
FTAN
90.51
-
82.78
-
92.41
88.82
Frequency-Temporal Attention Network for Remote Sensing Imagery Change Detection
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