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 1826–1850 of 3874 papers

TitleStatusHype
A Scale-Arbitrary Image Super-Resolution Network Using Frequency-domain Information—0
AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions—0
Kernel based low-rank sparse model for single image super-resolution—0
Improving Clinical Diagnosis Performance with Automated X-ray Scan Quality Enhancement Algorithms—0
Improving Generative Adversarial Networks for Video Super-Resolution—0
FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos—0
Improving Object Detection Quality in Football Through Super-Resolution Techniques—0
Continual Learning-Aided Super-Resolution Scheme for Channel Reconstruction and Generalization in OFDM Systems—0
A mathematical theory of resolution limits for super-resolution of positive sources—0
KernelFusion: Assumption-Free Blind Super-Resolution via Patch Diffusion—0
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging—0
Improving the resolution of microscope by deconvolution after dense scan—0
3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution—0
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
Incorporating Degradation Estimation in Light Field Spatial Super-Resolution—0
Kernel Aware Resampler—0
Kernelized Back-Projection Networks for Blind Super Resolution—0
FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization—0
Inductive Matrix Completion and Root-MUSIC-Based Channel Estimation for Intelligent Reflecting Surface (IRS)-Aided Hybrid MIMO Systems—0
Context Reasoning Attention Network for Image Super-Resolution—0
FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution—0
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution—0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
Content-decoupled Contrastive Learning-based Implicit Degradation Modeling for Blind Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified