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 3251–3300 of 3874 papers

TitleStatusHype
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-ResolutionCode0
Supervised Learning Based Super-Resolution DoA Estimation Utilizing Antenna Array Extrapolation—0
Robust Online Video Super-Resolution Using an Efficient Alternating Projections Scheme—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging—0
Robust Regression via Deep Negative Correlation Learning—0
DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors—0
Progressive Face Super-Resolution via Attention to Facial LandmarkCode0
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors—0
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution—0
RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-ResolutionCode0
Image Formation Model Guided Deep Image Super-ResolutionCode0
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement—0
Super-resolution of Omnidirectional Images Using Adversarial LearningCode0
Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing—0
Manifold Modeling in Embedded Space: A Perspective for Interpreting Deep Image PriorCode0
Attention-Aware Linear Depthwise Convolution for Single Image Super-Resolution—0
Architecture-aware Network Pruning for Vision Quality Applications—0
Multi-Contrast Super-Resolution MRI Through a Progressive Network—0
CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network—0
Content and Colour Distillation for Learning Image Translations with the Spatial Profile LossCode0
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement—0
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI—0
Is There Any Recovery Guarantee with Coupled Structured Matrix Factorization for Hyperspectral Super-Resolution?—0
Benefiting from Multitask Learning to Improve Single Image Super-Resolution—0
Image Enhancement by Recurrently-trained Super-resolution Network—0
Improved Super-Resolution Convolution Neural Network for Large Images—0
Learning Resolution-Invariant Deep Representations for Person Re-Identification—0
Image Super-Resolution Using a Wavelet-based Generative Adversarial NetworkCode0
Progressive Perception-Oriented Network for Single Image Super-ResolutionCode0
Light Field Super-resolution via Attention-Guided Fusion of Hybrid LensesCode0
A neural lens for super-resolution biological imaging—0
Super-Resolution Channel Estimation for Arbitrary Arrays in Hybrid Millimeter-Wave Massive MIMO Systems—0
Boosting Resolution and Recovering Texture of micro-CT Images with Deep Learning—0
DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal imagesCode0
Coupled-Projection Residual Network for MRI Super-Resolution—0
Hybrid Residual Attention Network for Single Image Super ResolutionCode0
Super-resolution meets machine learning: approximation of measures—0
Enhanced generative adversarial network for 3D brain MRI super-resolution—0
Gated Multiple Feedback Network for Image Super-ResolutionCode0
A Comparison of Super-Resolution and Nearest Neighbors Interpolation Applied to Object Detection on Satellite Data—0
Fully Convolutional Network for Removing DCT Artefacts From Images—0
FC^2N: Fully Channel-Concatenated Network for Single Image Super-ResolutionCode0
Multi-level Wavelet Convolutional Neural NetworksCode0
MRI Super-Resolution with Ensemble Learning and Complementary Priors—0
Improving the resolution of microscope by deconvolution after dense scan—0
Distilling with Residual Network for Single Image Super Resolution—0
Deep learning in ultrasound imaging—0
Super-Resolution of PROBA-V Images Using Convolutional Neural Networks—0
Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified