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 1776–1800 of 3874 papers

TitleStatusHype
ISTA-Inspired Network for Image Super-Resolution—0
Scene Text Image Super-Resolution via Content Perceptual Loss and Criss-Cross Transformer Blocks—0
CUF: Continuous Upsampling Filters—0
Action Matching: Learning Stochastic Dynamics from SamplesCode1
QMRNet: Quality Metric Regression for EO Image Quality Assessment and Super-ResolutionCode0
Face Super-Resolution with Progressive Embedding of Multi-scale Face Priors—0
A Comparative Study on 1.5T-3T MRI Conversion through Deep Neural Network Models—0
Efficient Image Super-Resolution using Vast-Receptive-Field AttentionCode1
Deep Fourier Up-SamplingCode0
DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images—0
Learning Texture Transformer Network for Light Field Super-Resolution—0
Cost-effective photonic super-resolution millimeter-wave joint radar-communication system using self-coherent detection—0
Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images—0
Flexible Alignment Super-Resolution Network for Multi-Contrast MRICode0
A Simple Plugin for Transforming Images to Arbitrary Scales—0
Single Image Super-Resolution Based on Capsule Neural NetworksCode1
Nanoscopic distribution of VAChT and VGLUT3 in striatal cholinergic varicosities suggests colocalization and segregation of the two transporters in synaptic vesicles—0
MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-ResolutionCode0
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter VideoCode1
Imagen Video: High Definition Video Generation with Diffusion Models—0
Accurate Image Restoration with Attention Retractable TransformerCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
Make-A-Video: Text-to-Video Generation without Text-Video DataCode1
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
Multi-scale Attention Network for Single Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified