Ephemeral182/ECCV24_T3-DiffWeather
[ECCV‘24] Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraint
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.
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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.
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45
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Language
Python
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Last pushed
Oct 30, 2024
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