YilinLiu97/FasterDIP-devil-in-upsampling
[ICCV2023] The Devil is in the upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior
This project helps image processing professionals enhance noisy images by identifying and removing visual disturbances. You input an image that needs cleaning, and it provides a denoised version, leveraging a deep image prior approach with optimized architectural decisions. It's designed for anyone working with digital images that require noise reduction as part of their workflow.
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Use this if you need to effectively denoise images and want to streamline the architectural choices for deep image prior models, especially for images with varying textures.
Not ideal if your primary task is image restoration types other than denoising, or if you require an extremely lightweight, real-time image processing solution.
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Language
Python
License
MIT
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Last pushed
Oct 15, 2023
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