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 2211–2220 of 3874 papers

TitleStatusHype
Kernel-aware Burst Blind Super-ResolutionCode0
Mitigating Channel-wise Noise for Single Image Super Resolution—0
Text Gestalt: Stroke-Aware Scene Text Image Super-ResolutionCode1
SphereSR: 360° Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation—0
Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical FlowCode1
Implicit Transformer Network for Screen Content Image Continuous Super-ResolutionCode1
Enhancing Multi-Scale Implicit Learning in Image Super-Resolution with Integrated Positional Encoding—0
Information Prebuilt Recurrent Reconstruction Network for Video Super-Resolution—0
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction—0
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-ResolutionCode1
Show:102550
← PrevPage 222 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified