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 1531–1540 of 3874 papers

TitleStatusHype
Super-Resolution Neural OperatorCode0
Stochastic Super-Resolution For Gaussian Textures—0
Single-photon Image Super-resolution via Self-supervised Learning—0
Consistency ModelsCode5
OPE-SR: Orthogonal Position Encoding for Designing a Parameter-free Upsampling Module in Arbitrary-scale Image Super-Resolution—0
Lessons Learned Report: Super-Resolution for Detection Tasks in Engineering Problem-Solving—0
Online Streaming Video Super-Resolution with Convolutional Look-Up Table—0
GRAN: Ghost Residual Attention Network for Single Image Super Resolution—0
TextIR: A Simple Framework for Text-based Editable Image Restoration—0
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified