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 381–390 of 3874 papers

TitleStatusHype
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIsCode1
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
Deep Image PriorCode1
Attention in Attention Network for Image Super-ResolutionCode1
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
Attentive Fine-Grained Structured Sparsity for Image RestorationCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
ARM: Any-Time Super-Resolution MethodCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified