Semantic Scholar Open Access 2022 917 sitasi

A Transformer-Based Siamese Network for Change Detection

W. G. C. Bandara Vishal M. Patel

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Abstrak

This paper presents a transformer-based Siamese network architecture (abbreviated by ChangeFormer) for Change Detection (CD) from a pair of co-registered remote sensing images. Different from recent CD frameworks, which are based on fully convolutional networks (ConvNets), the proposed method unifies hierarchically structured transformer encoder with Multi-Layer Perception (MLP) decoder in a Siamese network architecture to efficiently render multi-scale long-range details required for accurate CD. Experiments on two CD datasets show that the proposed end-to-end trainable ChangeFormer architecture achieves better CD performance than previous counterparts. Our code and pre-trained models are available at github.com/wgcban/ChangeFormer.

Topik & Kata Kunci

Computer Science

Penulis (2)

W. G. C. Bandara

Vishal M. Patel

Format Sitasi

APA MLA BibTeX

Bandara, W.G.C., Patel, V.M. (2022). A Transformer-Based Siamese Network for Change Detection. https://doi.org/10.1109/IGARSS46834.2022.9883686

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Lihat di Sumber doi.org/10.1109/IGARSS46834.2022.9883686

Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 917×
Sumber Database: Semantic Scholar
DOI: 10.1109/IGARSS46834.2022.9883686
Akses: Open Access ✓