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 2421–2430 of 3874 papers

TitleStatusHype
Compressed Domain Prior-Guided Video Super-Resolution for Cloud Gaming Content—0
MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D—0
Compressed Depth Map Super-Resolution and Restoration: AIM 2024 Challenge Results—0
MyStyle: A Personalized Generative Prior—0
N^2LoS: Single-Tag mmWave Backscatter for Robust Non-Line-of-Sight Localization—0
Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution—0
Compound Attention and Neighbor Matching Network for Multi-contrast MRI Super-resolution—0
Naive Bayes Super-Resolution Forest—0
Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles—0
Dynamic Attention-Guided Diffusion for Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified