Ephemeral182/ECCV24_T3-DiffWeather

[ECCV‘24] Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraint

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Experimental

This project helps professionals improve the clarity of images captured in challenging weather conditions like rain, haze, or snow. By inputting a degraded image, it produces a restored version where adverse weather effects are significantly reduced, revealing clearer details. It is designed for anyone who needs to analyze or use images taken outdoors in poor weather, such as those in autonomous driving, surveillance, or environmental monitoring.

No commits in the last 6 months.

Use this if you need to automatically enhance the visibility and detail in images that are obscured by various types of adverse weather.

Not ideal if your primary need is general image editing or object removal rather than specific weather degradation restoration.

adverse-weather-imaging outdoor-vision image-restoration surveillance autonomous-driving
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 3 / 25

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45

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1

Language

Python

License

Last pushed

Oct 30, 2024

Commits (30d)

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