The dataset is manually collected from Google Earth. It consists of six large bi-temporal high resolution images covering six cities (i.e., Beijing, Chengdu, Shenzhen, Chongqing, Wuhan, Xian) in China. The five large image-pairs (i.e., Beijing, Chengdu, Shenzhen, Chongqing, Wuhan) are clipped into 394 subimage pairs with sizes of 512×512. After data augmentation, a collection of 3940 bi-temporal image pairs is acquired. Xian image pair is clipped into 48 image pairs for model testing. There are 3600 image pairs in the training dataset, 340 image paris in the validation dataset, and 48 image pairs in the test dataset.
Variants: DSIFN-CD
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Change Detection | CDMaskFormer | Rethinking Remote Sensing Change Detection … | 2024-06-21 |
| Change Detection | C2FNet | C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change … | 2024-04-22 |
| Change Detection | HANet | HANet: A Hierarchical Attention Network … | 2024-04-14 |
| Change Detection | CGNet | Change Guiding Network: Incorporating Change … | 2024-04-14 |
| Change Detection | HCGMNet | HCGMNET: A Hierarchical Change Guiding … | 2023-02-21 |
| Change Detection | SARAS-Net | SARAS-Net: Scale and Relation Aware … | 2022-12-02 |
| Change Detection | DDPM-CD | DDPM-CD: Denoising Diffusion Probabilistic Models … | 2022-06-23 |
Recent papers with results on this dataset: