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

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Showing 3601–3650 of 3874 papers

TitleStatusHype
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Efficient Video Super-Resolution for Real-time Rendering with Decoupled G-buffer Guidance—0
Temporal and Spatial Super Resolution with Latent Diffusion Model in Medical MRI images—0
Fast and selective super-resolution ultrasound in vivo with sono-switchable nanodroplets—0
WaveDiffUR: A diffusion SDE-based solver for ultra magnification super-resolution in remote sensing images—0
Efficient Two-Dimensional Line Spectrum Estimation Based on Decoupled Atomic Norm Minimization—0
Wavelet-Based Segmentation on the Sphere—0
EfficientTempNet: Temporal Super-Resolution of Radar Rainfall—0
Fast Image Deconvolution using Hyper-Laplacian Priors—0
Diffusion Models, Image Super-Resolution And Everything: A Survey—0
Fast Image Super-Resolution Based on In-Place Example Regression—0
Efficient Super Resolution Using Binarized Neural Network—0
Efficient Super Resolution For Large-Scale Images Using Attentional GAN—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Efficient Terrain Stochastic Differential Efficient Terrain Stochastic Differential Equations for Multipurpose Digital Elevation Model Restoration—0
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Fast Randomized-MUSIC for mm-Wave Massive MIMO Radars—0
Advancing biological super-resolution microscopy through deep learning: a brief review—0
Fast Single Image Super-Resolution—0
Fast single image super-resolution based on sigmoid transformation—0
Fast Spatio-Temporal Residual Network for Video Super-Resolution—0
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline—0
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Advances on CNN-based super-resolution of Sentinel-2 images—0
Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light—0
Temporal Super-Resolution using Multi-Channel Illumination Source—0
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution—0
Efficient Star Distillation Attention Network for Lightweight Image Super-Resolution—0
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution—0
Feature-based Recognition Framework for Super-resolution Images—0
EfficientSRFace: An Efficient Network with Super-Resolution Enhancement for Accurate Face Detection—0
Feature-Driven Super-Resolution for Object Detection—0
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review—0
Efficient Single Image Super-Resolution with Entropy Attention and Receptive Field Augmentation—0
Feature Representation Matters: End-to-End Learning for Reference-based Image Super-resolution—0
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces—0
Feature Super-Resolution: Make Machine See More Clearly—0
Federated Learning for Blind Image Super-Resolution—0
Efficient OCT Image Segmentation Using Neural Architecture Search—0
Feedback Graph Attention Convolutional Network for Medical Image Enhancement—0
Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization—0
Efficient neural supersampling on a novel gaming dataset—0
Feedback Neural Network based Super-resolution of DEM for generating high fidelity features—0
Feedback Pyramid Attention Networks for Single Image Super-Resolution—0
Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer—0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified