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 1101–1125 of 3874 papers

TitleStatusHype
Multi-level Wavelet Convolutional Neural NetworksCode0
Multi-Modality Image Super-Resolution using Generative Adversarial NetworksCode0
Multi-scale deep neural networks for real image super-resolutionCode0
Denoising Prior Driven Deep Neural Network for Image RestorationCode0
Multi Kernel Estimation based Object SegmentationCode0
Denoising Graph Super-Resolution towards Improved Collider Event ReconstructionCode0
Accelerating the Training of Video Super-Resolution ModelsCode0
Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-ResolutionCode0
Multigrid Backprojection Super-Resolution and Deep Filter VisualizationCode0
Denoiser-based projections for 2-D super-resolution multi-reference alignmentCode0
A Multi-Pass GAN for Fluid Flow Super-ResolutionCode0
Multiframe Motion Coupling for Video Super ResolutionCode0
Multi-level Wavelet-CNN for Image RestorationCode0
Multi-scale Residual Network for Image Super-ResolutionCode0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
A Motion Assessment Method for Reference Stack Selection in Fetal Brain MRI Reconstruction Based on Tensor Rank ApproximationCode0
Binary Document Image Super Resolution for Improved Readability and OCR PerformanceCode0
MRI Super-Resolution using Multi-Channel Total VariationCode0
MR Slice Profile Estimation by Learning to Match Internal Patch DistributionsCode0
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural NetworksCode0
Deformable Non-local Network for Video Super-ResolutionCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification LayersCode0
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
Multi-scale super-resolution generation of low-resolution scanned pathological imagesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified