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 331–340 of 3874 papers

TitleStatusHype
Deep Blind Super-Resolution for Satellite VideoCode1
Learning Large-Factor EM Image Super-Resolution with Generative PriorsCode1
Look-Up Table Compression for Efficient Image RestorationCode1
Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real WorldCode1
Revisiting Spatial-Frequency Information Integration from a Hierarchical Perspective for Panchromatic and Multi-Spectral Image FusionCode1
Noise-free Optimization in Early Training Steps for Image Super-ResolutionCode1
KeDuSR: Real-World Dual-Lens Super-Resolution via Kernel-Free MatchingCode1
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned GuidanceCode1
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization PerspectiveCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified