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 821–830 of 3874 papers

TitleStatusHype
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-ResolutionCode1
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical FlowCode1
Dual-Camera Super-Resolution with Aligned Attention ModulesCode1
Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANsCode1
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and ResultsCode1
Deep Image PriorCode1
NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and ResultsCode1
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIsCode1
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified