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 2591–2600 of 3874 papers

TitleStatusHype
Super-Resolving Beyond Satellite Hardware Using Realistically Degraded Images—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
Deep learning-based super-resolution fluorescence microscopy on small datasetsCode0
Feedback Refined Local-Global Network for Super-Resolution of Hyperspectral ImageryCode0
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data CharacteristicCode1
Generating Images with Sparse RepresentationsCode1
Super-resolution Method for Coherent DOA Estimation of Multiple Wideband Sources—0
Super-Resolution DOA Estimation for Wideband Signals using Arbitrary Linear Arrays without Focusing Matrices—0
Real-World Single Image Super-Resolution: A Brief ReviewCode1
Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution EnhancementCode1
Show:102550
← PrevPage 260 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified