Z-Zheng/ChangeStar

Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery (ICCV 2021) https://arxiv.org/abs/2108.07002

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Emerging

This helps remote sensing analysts or disaster response teams quickly identify significant changes in satellite or aerial imagery. You provide an image (or two for comparison) and it highlights where objects like buildings or infrastructure have appeared or disappeared. It's used by professionals who need to detect changes from high-resolution remote sensing data.

191 stars. No commits in the last 6 months.

Use this if you need to automatically spot and map changes in geospatial objects using high-resolution satellite or drone images, even when you only have a single recent image and past data is limited.

Not ideal if your primary goal is general object detection within an image without focusing on changes over time, or if you're working with low-resolution imagery.

remote-sensing geospatial-analysis disaster-assessment urban-monitoring environmental-change
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

191

Forks

33

Language

Python

License

Apache-2.0

Last pushed

May 10, 2022

Commits (30d)

0

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