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 461–470 of 3874 papers

TitleStatusHype
Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-ResolutionCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
Tunable Convolutions with Parametric Multi-Loss OptimizationCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
CoReFusion: Contrastive Regularized Fusion for Guided Thermal Super-ResolutionCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation TransformerCode1
Cascaded Local Implicit Transformer for Arbitrary-Scale Super-ResolutionCode1
CuNeRF: Cube-Based Neural Radiance Field for Zero-Shot Medical Image Arbitrary-Scale Super ResolutionCode1
Single-subject Multi-contrast MRI Super-resolution via Implicit Neural RepresentationsCode1
Show:102550
← PrevPage 47 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified