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

Showing 12261250 of 3874 papers

TitleStatusHype
Deep Back-Projection Networks for Single Image Super-resolutionCode0
AIM 2019 Challenge on Constrained Super-Resolution: Methods and ResultsCode0
MetH: A family of high-resolution and variable-shape image challengesCode0
Audio Super Resolution using Neural NetworksCode0
Decoupling Fine Detail and Global Geometry for Compressed Depth Map Super-ResolutionCode0
Decouple Learning for Parameterized Image OperatorsCode0
MemNet: A Persistent Memory Network for Image RestorationCode0
Decimated Framelet System on Graphs and Fast G-Framelet TransformsCode0
Attention Based Real Image RestorationCode0
Medical Image Imputation from Image CollectionsCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRICode0
Masked Autoencoders are PDE LearnersCode0
Maximum Likelihood on the Joint (Data, Condition) Distribution for Solving Ill-Posed Problems with Conditional Flow ModelsCode0
Attention-based Multi-Reference Learning for Image Super-ResolutionCode0
MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-ResolutionCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and EnhancementCode0
Mining self-similarity: Label super-resolution with epitomic representationsCode0
Multiframe Motion Coupling for Video Super ResolutionCode0
MAANet: Multi-view Aware Attention Networks for Image Super-ResolutionCode0
Data Upcycling Knowledge Distillation for Image Super-ResolutionCode0
Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approachCode0
Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-DesignCode0
Data-Free Knowledge Distillation for Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified