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 1581–1590 of 3874 papers

TitleStatusHype
Image Super-Resolution as a Defense Against Adversarial AttacksCode0
C2PD: Continuity-Constrained Pixelwise Deformation for Guided Depth Super-ResolutionCode0
Hyperspectral Image Super-Resolution With Optimized RGB GuidanceCode0
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix EstimationCode0
Hyperspectral and multispectral image fusion with arbitrary resolution through self-supervised representationsCode0
Hybrid Residual Attention Network for Single Image Super ResolutionCode0
DSR-Diff: Depth Map Super-Resolution with Diffusion ModelCode0
A Diffusion-Driven Temporal Super-Resolution and Spatial Consistency Enhancement Framework for 4D MRI imagingCode0
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-ResolutionCode0
HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area SurveillanceCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified