This is the Pytorch implementation of Remote Sensing Change Detection using Denoising Diffusion Probabilistic Models. The generated images contain objects that we commonly see in real remote sensing images, such as buildings, trees, roads, vegetation, water surfaces, etc., demonstrating the powerful ability of the diffusion models to extract key semantics that can be further used in remote sensing change detection. We fine-tune a light-weight change detection head which takes multi-level feature representations from the pre-trained diffusion model as inputs and outputs change prediction map.

Features

  • Train diffusion model with remote sensing data
  • Collect off-the-shelf remote sensing data to train diffusion model
  • Training/Resume unconditional diffusion model on remote sensing data
  • Sampling from the diffusion model
  • Provide the path to pre-trained diffusion model
  • Train the change detection network

Project Samples

Project Activity

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Categories

Change Detection

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Change Detection Tool

Registered

2023-10-19