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홈
SOTA
Change Detection
Change Detection On Whu Cd
Change Detection On Whu Cd
평가 지표
F1
IoU
Overall Accuracy
Precision
Recall
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
F1
IoU
Overall Accuracy
Precision
Recall
Paper Title
Repository
CDMaskFormer
91.56
84.44
99.23
92.25
90.89
Rethinking Remote Sensing Change Detection With A Mask View
DDLNet
90.56
82.75
99.13
91.56
90.03
DDLNet: Boosting Remote Sensing Change Detection with Dual-Domain Learning
Tiny-CD
91.05
83.57
99.10
92.68
89.47
TINYCD: A (Not So) Deep Learning Model For Change Detection
HANet
88.16
78.82
99.16
88.30
88.01
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
LRNet
92.51
86.06
99.47
95.11
90.04
LRNet: Change detection of high-resolution remote sensing imagery via strategy of localization-then-refinement
-
CGNet
92.59
86.21
99.48
94.47
90.79
Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery
RSM-CD
91.87
84.96
-
93.37
90.42
RS-Mamba for Large Remote Sensing Image Dense Prediction
T-UNet
91.77
-
99.42
95.44
88.37
T-UNet: Triplet UNet for Change Detection in High-Resolution Remote Sensing Images
CLAFA-LWGANet L2
95.24
90.92
-
96.51
-
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
BiFA
94.37
89.34
99.56
95.15
93.60
BiFA: Remote Sensing Image Change Detection With Bitemporal Feature Alignment
DTCDSCN
89.75
81.40
-
90.15
89.35
Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model
-
DDPM-CD
92.65
-
99.42
-
-
DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
ChangeMamba
94.19
89.02
99.58
96.18
92.23
ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model
Dsfer-Net
92.58
86.18
99.46
94.17
91.04
Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks
C2FNet
94.36
89.33
99.56
96.57
92.26
C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
STNet
87.46
77.72
98.85
87.84
87.08
STNet: Spatial and Temporal feature fusion network for change detection in remote sensing images
HCGMNet
92.08
85.33
99.45
93.93
90.31
HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
SRC-Net
92.06
85.28
99.30
92.57
91.55
SRC-Net: Bi-Temporal Spatial Relationship Concerned Network for Change Detection
RFL-CDNet
91.39
-
-
91.33
91.46
RFL-CDNet: Towards Accurate Change Detection via Richer Feature Learning
-
CDMamba
93.76
88.26
99.51
95.58
92.01
CDMamba: Remote Sensing Image Change Detection with Mamba
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