Shypd.aiThe largest open index of AI toolsSingle-Image-Super-Resolution is a collection of high-impact and state-of-the-art single image super-resolution methods. It provides resources for example-based SR, including early learning-based, sparsity-based, and deep architecture methods.
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Single-Image-Super-Resolution is a comprehensive collection of resources dedicated to single image super-resolution (SISR) techniques. Inspired by prominent computer vision repositories, this tool compiles high-impact and state-of-the-art methods, making it an invaluable resource for researchers and developers. It categorizes methods into several key areas, including early learning-based approaches that established the foundational framework, sparsity-based methods utilizing techniques like sparse coding, and self-exemplar methods. A significant portion is dedicated to deep architectures, showcasing the evolution of CNNs, GANs, and other advanced deep learning models for enhancing image resolution and quality. The collection also includes survey papers and provides links to research papers and code implementations where available, facilitating deeper exploration and practical application of these SR methods.
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