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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 871–880 of 3874 papers

TitleStatusHype
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
Accelerating Diffusion Models for Inverse Problems through Shortcut SamplingCode1
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
EDPN: Enhanced Deep Pyramid Network for Blurry Image RestorationCode1
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark DatasetCode1
Efficient and Degradation-Adaptive Network for Real-World Image Super-ResolutionCode1
Edge and Identity Preserving Network for Face Super-ResolutionCode1
Real-Time Super-Resolution System of 4K-Video Based on Deep LearningCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
EBSR: Feature Enhanced Burst Super-Resolution With Deformable AlignmentCode1
Show:102550
← PrevPage 88 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified