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 3201–3250 of 3874 papers

TitleStatusHype
Deeply Matting-based Dual Generative Adversarial Network for Image and Document Label Supervision—0
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network—0
TextSR: Content-Aware Text Super-Resolution Guided by RecognitionCode1
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator—0
Phase Retrieval using Untrained Neural Network Priors—0
Blind Super-Resolution Kernel Estimation using an Internal-GANCode0
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise ModulationsCode0
Edge-Informed Single Image Super-ResolutionCode0
Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors—0
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR VideoCode0
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations—0
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
Learning Filter Basis for Convolutional Neural Network CompressionCode1
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
Image Formation Model Guided Deep Image Super-ResolutionCode0
RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-ResolutionCode0
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement—0
A Tour of Convolutional Networks Guided by Linear InterpretersCode2
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
Improved Super-Resolution Convolution Neural Network for Large Images—0
Image Enhancement by Recurrently-trained Super-resolution Network—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
Learned Image Downscaling for Upscaling using Content Adaptive ResamplerCode1
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified