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 2026–2050 of 3874 papers

TitleStatusHype
Cutting-Edge Techniques for Depth Map Super-Resolution—0
Semantic Segmentation Using Super Resolution Technique as Pre-Processing—0
Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging SystemsCode0
Iterative-in-Iterative Super-Resolution Biomedical Imaging Using One Real Image—0
Store and Fetch Immediately: Everything Is All You Need for Space-Time Video Super-resolutionCode0
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
Directional diffusion models for graph representation learning—0
Super-Resolution of BVOC Emission Maps Via Domain AdaptationCode0
DiffuseIR:Diffusion Models For Isotropic Reconstruction of 3D Microscopic Images—0
HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology—0
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models—0
Optical Coherence Tomography Image Enhancement via Block Hankelization and Low Rank Tensor Network Approximation—0
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach—0
CANDID: Correspondence AligNment for Deep-burst Image Denoising—0
Generalizable One-shot Neural Head Avatar—0
Effects of Data Enrichment with Image Transformations on the Performance of Deep Networks—0
Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration—0
SARN: Structurally-Aware Recurrent Network for Spatio-Temporal DisaggregationCode0
A Unified Framework to Super-Resolve Face Images of Varied Low Resolutions—0
SwinRDM: Integrate SwinRNN with Diffusion Model towards High-Resolution and High-Quality Weather Forecasting—0
AI Techniques for Cone Beam Computed Tomography in Dentistry: Trends and Practices—0
ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes—0
Scale Guided Hypernetwork for Blind Super-Resolution Image Quality AssessmentCode0
Show:102550
← PrevPage 82 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified