https://github.com/wgcban/metric-cd

Official PyTorch implementation of Deep Metric Learning for Unsupervised Change Detection in Remote Sensing Images
https://github.com/wgcban/metric-cd

change-detection metric-learning remote-sensing unsupervised-learning

Last synced: 5 months ago
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Official PyTorch implementation of Deep Metric Learning for Unsupervised Change Detection in Remote Sensing Images

• Host: GitHub
• URL: https://github.com/wgcban/metric-cd
• Owner: wgcban
• Created: 2021-11-22T20:51:32.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2024-12-08T18:50:30.000Z (10 months ago)
• Last Synced: 2025-03-31T08:44:08.366Z (7 months ago)
• Topics: change-detection, metric-learning, remote-sensing, unsupervised-learning
• Language: Jupyter Notebook
• Homepage: https://arxiv.org/abs/2303.09536
• Size: 60.2 MB
• Stars: 18
• Watchers: 1
• Forks: 4
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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README

          
# Deep Metric Learning for Unsupervised CD (WACV'25)

Official PyTorch implementation of "Deep Metric Learning for Unsupervised Change Detection in Remote Sensing Images" (Metric-CD)

paper: https://arxiv.org/abs/2303.09536

# Introduction



  

   

   

  



Figure 1. Demonstration of how our proposed algorithm finds changes in the multi-temporal remote sensing image (for beirut image pair in OSCD dataset).


# Demo on OSCD dataset

## Conda environment.

Create a virtual conda environment using the provided environment.yml (you may use: conda env create -f environment.yml).

## Run Demo.

Once the environment is setup, open Demo_OSCD from jupyter notebook and simply run the file.