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 2221–2230 of 3874 papers

TitleStatusHype
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Physics Driven Deep Retinex Fusion for Adaptive Infrared and Visible Image FusionCode1
A Survey on Deep learning based Document Image Enhancement—0
Label-Efficient Semantic Segmentation with Diffusion ModelsCode1
PP-MSVSR: Multi-Stage Video Super-ResolutionCode3
Feature-based Recognition Framework for Super-resolution Images—0
Towards Super-Resolution CEST MRI for Visualization of Small StructuresCode0
Fast Neural Representations for Direct Volume RenderingCode1
High-Resolution WiFi Imaging with Reconfigurable Intelligent Surfaces—0
Conditional Generation Using Polynomial ExpansionsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified