Change Detection On Whu Cd

Metrics

IoU

Overall Accuracy

Precision

Recall

Results

Performance results of various models on this benchmark

						Paper Title	Repository
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	-
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
ChangeMamba	94.19	89.02	99.58	96.18	92.23	ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model
CDMamba	93.76	88.26	99.51	95.58	92.01	CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection
DDPM-CD	92.65	-	99.42	-	-	DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
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
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
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
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
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
CDMaskFormer	91.56	84.44	99.23	92.25	90.89	Rethinking Remote Sensing Change Detection With A Mask View
RFL-CDNet	91.39	-	-	91.33	91.46	RFL-CDNet: Towards Accurate Change Detection via Richer Feature Learning
Tiny-CD	91.05	83.57	99.10	92.68	89.47	TINYCD: A (Not So) Deep Learning Model For Change Detection
DDLNet	90.56	82.75	99.13	91.56	90.03	DDLNet: Boosting Remote Sensing Change Detection with Dual-Domain Learning
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	-
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
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

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Change Detection On Whu Cd

Metrics

Results