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 2651–2700 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
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows—0
PNEN: Pyramid Non-Local Enhanced Networks—0
Blind Restoration of High-Resolution Ultrasound Video—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
PointSAGE: Mesh-independent superresolution approach to fluid flow predictions—0
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
Polyblur: Removing mild blur by polynomial reblurring—0
Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration—0
Likelihood Annealing: Fast Calibrated Uncertainty for Regression—0
Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint—0
Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report—0
Blind inverse problems with isolated spikes—0
UnmixingSR: Material-aware Network with Unsupervised Unmixing as Auxiliary Task for Hyperspectral Image Super-resolution—0
Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST—0
Blind Image Super-Resolution with Spatial Context Hallucination—0
Predicting Future States with Spatial Point Processes in Single Molecule Resolution Spatial Transcriptomics—0
Predicting Stress in Two-phase Random Materials and Super-Resolution Method for Stress Images by Embedding Physical Information—0
Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification—0
Prediction-assistant Frame Super-Resolution for Video Streaming—0
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
Blind Image Super-Resolution via Contrastive Representation Learning—0
Blind Image Super-Resolution: A Survey and Beyond—0
Prior Knowledge Distillation Network for Face Super-Resolution—0
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis—0
Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified