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 3051–3060 of 3874 papers

TitleStatusHype
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
Novel Super-Resolution Method Based on High Order Nonlocal-Means—0
NSD-DIL: Null-Shot Deblurring Using Deep Identity Learning—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results—0
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results—0
NTIRE 2021 Challenge on Video Super-Resolution—0
NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results—0
NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results—0
NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution—0
Show:102550
← PrevPage 306 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified