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 771–780 of 3874 papers

TitleStatusHype
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
Lightweight Modules for Efficient Deep Learning based Image RestorationCode1
Attention in Attention Network for Image Super-ResolutionCode1
Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing StrategyCode1
A Benchmark for Chinese-English Scene Text Image Super-resolutionCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
Attentive Fine-Grained Structured Sparsity for Image RestorationCode1
LKFormer: Large Kernel Transformer for Infrared Image Super-ResolutionCode1
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified