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 3671–3680 of 3874 papers

TitleStatusHype
FlashSR: One-step Versatile Audio Super-resolution via Diffusion Distillation—0
Advanced Underwater Image Quality Enhancement via Hybrid Super-Resolution Convolutional Neural Networks and Multi-Scale Retinex-Based Defogging Techniques—0
Efficient Model Agnostic Approach for Implicit Neural Representation Based Arbitrary-Scale Image Super-Resolution—0
Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution—0
FL-MISR: Fast Large-Scale Multi-Image Super-Resolution for Computed Tomography Based on Multi-GPU Acceleration—0
Efficient Medicinal Image Transmission and Resolution Enhancement via GAN—0
Text-guided Explorable Image Super-resolution—0
FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution—0
Show:102550
← PrevPage 368 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified