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 3821–3830 of 3874 papers

TitleStatusHype
Single Image Super-Resolution From Transformed Self-Exemplars—0
Modeling Deformable Gradient Compositions for Single-Image Super-Resolution—0
Robust Multi-Image Based Blind Face Hallucination—0
Robust Image Filtering Using Joint Static and Dynamic Guidance—0
Beyond Principal Components: Deep Boltzmann Machines for Face Modeling—0
Metric Imitation by Manifold Transfer for Efficient Vision Applications—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
Sparse Depth Super Resolution—0
Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning—0
Transport-Based Single Frame Super Resolution of Very Low Resolution Face Images—0
Show:102550
← PrevPage 383 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified