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 1791–1800 of 3874 papers

TitleStatusHype
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution—0
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions—0
OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing—0
Efficient Image Super-Resolution via Symmetric Visual Attention Network—0
No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy—0
Sparsity-based background removal for STORM super-resolution imagesCode0
City Scene Super-Resolution via Geometric Error MinimizationCode0
TriNeRFLet: A Wavelet Based Triplane NeRF Representation—0
Frequency-Time Diffusion with Neural Cellular Automata—0
AGG: Amortized Generative 3D Gaussians for Single Image to 3D—0
Show:102550
← PrevPage 180 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified