HCGMNET: A Hierarchical Change Guiding Map Network For Change Detection
Chengxi Han, Chen Wu, Bo Du
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ReproduceCode
- github.com/ChengxiHAN/HCGMNet-CDOfficialpytorch★ 32
Abstract
Very-high-resolution (VHR) remote sensing (RS) image change detection (CD) has been a challenging task for its very rich spatial information and sample imbalance problem. In this paper, we have proposed a hierarchical change guiding map network (HCGMNet) for change detection. The model uses hierarchical convolution operations to extract multiscale features, continuously merges multi-scale features layer by layer to improve the expression of global and local information, and guides the model to gradually refine edge features and comprehensive performance by a change guide module (CGM), which is a self-attention with changing guide map. Extensive experiments on two CD datasets show that the proposed HCGMNet architecture achieves better CD performance than existing state-of-the-art (SOTA) CD methods.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| CDD Dataset (season-varying) | HCGMNet | F1-Score | 95.07 | — | Unverified |
| DSIFN-CD | HCGMNet | F1 | 55 | — | Unverified |
| GoogleGZ-CD | HCGMNet | F1 | 85.71 | — | Unverified |
| LEVIR+ | HCGMNet | F1 | 82.37 | — | Unverified |
| LEVIR-CD | HCGMNet | F1 | 91.77 | — | Unverified |
| S2Looking | HCGMNet | F1-Score | 63.87 | — | Unverified |
| SYSU-CD | HCGMNet | F1 | 79.76 | — | Unverified |
| WHU-CD | HCGMNet | F1 | 92.08 | — | Unverified |