computer-vision-14
Deblurring
3260 papers • 126 benchmarks • 313 datasets
Deblurring is a computer vision task that involves removing the blurring artifacts from images or videos to restore the original, sharp content. Blurring can be caused by various factors such as camera shake, fast motion, and out-of-focus objects, and can result in a loss of detail and quality in the captured images. The goal of deblurring is to produce a clear, high-quality image that accurately represents the original scene. ( Image credit: Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks )
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in deblurring-14
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Dataset
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Actions
GoPro
GoPro
RealBlur-R (trained on GoPro)
RealBlur-R (trained on GoPro)
HIDE (trained on GOPRO)
Libraries
iUse these libraries to find deblurring-14 models and implementations
3 papers 348
