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 1301–1325 of 3874 papers

TitleStatusHype
Continual Learning Approaches for Anomaly DetectionCode0
Handheld Multi-Frame Super-ResolutionCode0
Lightweight Feature Fusion Network for Single Image Super-ResolutionCode0
AFN: Attentional Feedback Network based 3D Terrain Super-ResolutionCode0
Lightweight Image Super-Resolution with Adaptive Weighted Learning NetworkCode0
Manifold Modeling in Embedded Space: A Perspective for Interpreting Deep Image PriorCode0
Content and Colour Distillation for Learning Image Translations with the Spatial Profile LossCode0
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational InferenceCode0
Constraint matrix factorization for space variant PSFs field restorationCode0
Leveraging Segment Anything Model in Identifying Buildings within Refugee Camps (SAM4Refugee) from Satellite Imagery for Humanitarian OperationsCode0
AFFIRM: Affinity Fusion-based Framework for Iteratively Random Motion correction of multi-slice fetal brain MRICode0
Lightweight and Efficient Image Super-Resolution with Block State-based Recursive NetworkCode0
A Review of Convolutional Neural Networks for Inverse Problems in ImagingCode0
Exploring Linear Attention Alternative for Single Image Super-ResolutionCode0
Learning to Super Resolve Intensity Images from EventsCode0
Conditioning and Sampling in Variational Diffusion Models for Speech Super-ResolutionCode0
Explorable Super ResolutionCode0
A Comprehensive End-to-End Computer Vision Framework for Restoration and Recognition of Low-Quality Engineering DrawingsCode0
Learning Parallax Attention for Stereo Image Super-ResolutionCode0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Learning Series-Parallel Lookup Tables for Efficient Image Super-ResolutionCode0
Lightweight and Robust Representation of Economic Scales from Satellite ImageryCode0
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super ResolutionCode0
A Regularized Conditional GAN for Posterior Sampling in Image Recovery ProblemsCode0
Exemplar Guided Face Image Super-Resolution without Facial LandmarksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified