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 2771–2780 of 3874 papers

TitleStatusHype
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning—0
Super-resolved multi-temporal segmentation with deep permutation-invariant networks—0
Super-resolved virtual staining of label-free tissue using diffusion models—0
Super Resolve Dynamic Scene From Continuous Spike Streams—0
Super-resolving 2D stress tensor field conserving equilibrium constraints using physics informed U-Net—0
Super-Resolving Beyond Satellite Hardware Using Realistically Degraded Images—0
Super-Resolving Blurry Images with Events—0
Super-Resolving Commercial Satellite Imagery Using Realistic Training Data—0
Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar—0
Super-Resolving Noisy Images—0
Show:102550
← PrevPage 278 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified