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 3426–3450 of 3874 papers

TitleStatusHype
A Survey of Deep Learning Video Super-Resolution—0
Volumetric Image Projection Super-Resolution Ultrasound (VIP-SR) with a 1D Unfocused Linear Array—0
Super-resolution with Sparse Arrays: A Non-Asymptotic Analysis of Spatio-temporal Trade-offs—0
Super-Resolution with Structured Motion—0
Super-Resolution works for coastal simulations—0
Super-resolved Localisation without Identifying LoS/NLoS Paths—0
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
AGG: Amortized Generative 3D Gaussians for Single Image to 3D—0
Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar—0
ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields—0
Super-Resolving Noisy Images—0
Volumetric Super-Resolution of Multispectral Data—0
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach—0
Super-Resolving Very Low-Resolution Face Images With Supplementary Attributes—0
SuperTran: Reference Based Video Transformer for Enhancing Low Bitrate Streams in Real Time—0
Supervised Deep Kriging for Single-Image Super-Resolution—0
Supervised Learning Based Super-Resolution DoA Estimation Utilizing Antenna Array Extrapolation—0
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering—0
Show:102550
← PrevPage 138 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified