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 2651–2675 of 3874 papers

TitleStatusHype
Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks—0
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration—0
PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study—0
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report—0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Boosting Resolution and Recovering Texture of micro-CT Images with Deep Learning—0
Boosting Optical Character Recognition: A Super-Resolution Approach—0
Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors—0
Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution—0
Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution—0
Pixel Co-Occurence Based Loss Metrics for Super Resolution Texture Recovery—0
Boosting Diffusion-Based Text Image Super-Resolution Model Towards Generalized Real-World Scenarios—0
Boomerang: Local sampling on image manifolds using diffusion models—0
Super-resolution of Time-series Labels for Bootstrapped Event Detection—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns—0
BOLD: Boolean Logic Deep Learning—0
Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling—0
Supervised Image Translation from Visible to Infrared Domain for Object Detection—0
Block-Based Multi-Scale Image Rescaling—0
Plasma Surrogate Modelling using Fourier Neural Operators—0
Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applications—0
Blind Time-of-Flight Imaging: Sparse Deconvolution on the Continuum with Unknown Kernels—0
Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution—0
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Show:102550
← PrevPage 107 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified