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SOTA
Change Detection
Change Detection On Cdd Dataset Season 1
Change Detection On Cdd Dataset Season 1
评估指标
F1-Score
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
F1-Score
Paper Title
Repository
SGSLN/512
97.77
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial Localization
MAE+MTP(ViT-B+RVSA)
97.87
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
ChangeCLIP
97.89
ChangeCLIP: Remote sensing change detection with multimodal vision-language representation learning
MAE+MTP(ViT-L+RVSA)
97.98
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
HANet
89.23
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
C2FNet
95.93
C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
SGSLN/128
93.76
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial Localization
DDPM-CD
95.62
DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
SGSLN/256
96.24
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial Localization
IMP+MTP(InternImage-XL)
98.33
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
P2V-CD
98.42
Transition Is a Process: Pair-to-Video Change Detection Networks for Very High Resolution Remote Sensing Images
HCGMNet
95.07
HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
CGNet
94.73
Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
SNUNet-c48
96.2
SNUNet-CD: A Densely Connected Siamese Network for Change Detection of VHR Images
ESCNet
93.54
ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images
SNUNet-c32
95.3
SNUNet-CD: A Densely Connected Siamese Network for Change Detection of VHR Images
0 of 16 row(s) selected.
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