SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 3851–3860 of 3874 papers

TitleStatusHype
Image-based Synthesis and Re-Synthesis of Viewpoints Guided by 3D Models—0
Super-Resolving Noisy Images—0
Similarity-Aware Patchwork Assembly for Depth Image Super-Resolution—0
High Resolution 3D Shape Texture from Multiple Videos—0
Single Image Super-resolution using Deformable Patches—0
A Reverse Hierarchy Model for Predicting Eye Fixations—0
Structure Tensor Based Image Interpolation Method—0
Sparse Coding Approach for Multi-Frame Image Super Resolution—0
Single image super resolution in spatial and wavelet domain—0
New Algorithms for Learning Incoherent and Overcomplete Dictionaries—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified