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 1126–1150 of 3874 papers

TitleStatusHype
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
Multiframe Motion Coupling for Video Super ResolutionCode0
Multigrid Backprojection Super-Resolution and Deep Filter VisualizationCode0
Multi Kernel Estimation based Object SegmentationCode0
DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal imagesCode0
DeepSTORM3D: dense three dimensional localization microscopy and point spread function design by deep learningCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR ApplicationsCode0
MRI Super-Resolution using Multi-Channel Total VariationCode0
Deep Sparse and Low-Rank Prior for Hyperspectral Image DenoisingCode0
MR Slice Profile Estimation by Learning to Match Internal Patch DistributionsCode0
Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-ResolutionCode0
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural NetworksCode0
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification LayersCode0
Beyond Subspace Isolation: Many-to-Many Transformer for Light Field Image Super-resolutionCode0
Deep Residual Network for Joint Demosaicing and Super-ResolutionCode0
Model-Guided Network with Cluster-Based Operators for Spatio-Spectral Super-ResolutionCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Unsupervised Hyperspectral and Multispectral Image Fusion via Self-Supervised Modality DecouplingCode0
Deep learning Framework for Mobile MicroscopyCode0
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold SimplificationCode0
Multi-level Wavelet-CNN for Image RestorationCode0
Mining self-similarity: Label super-resolution with epitomic representationsCode0
MetH: A family of high-resolution and variable-shape image challengesCode0
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problemsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified