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 1476–1500 of 3874 papers

TitleStatusHype
Frequency-Time Diffusion with Neural Cellular Automata—0
Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution—0
From Blurry to Brilliant Detection: YOLOv5-Based Aerial Object Detection with Super Resolution—0
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions—0
Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures—0
A survey of machine learning-based physics event generation—0
From General to Specific: Online Updating for Blind Super-Resolution—0
From Image- to Pixel-level: Label-efficient Hyperspectral Image Reconstruction—0
From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes—0
CUF: Continuous Upsampling Filters—0
A GPU-Accelerated Light-field Super-resolution Framework Based on Mixed Noise Model and Weighted Regularization—0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
FNOSeg3D: Resolution-Robust 3D Image Segmentation with Fourier Neural Operator—0
FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring—0
A Generative Adversarial Network for AI-Aided Chair Design—0
High-Resolution Be Aware! Improving the Self-Supervised Real-World Super-Resolution—0
Functional Nonlinear Sparse Models—0
Fluctuation-based deconvolution in fluorescence microscopy using plug-and-play denoisers—0
Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution—0
FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements—0
Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images—0
Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution—0
GameIR: A Large-Scale Synthesized Ground-Truth Dataset for Image Restoration over Gaming Content—0
A super-resolution reconstruction method for lightweight building images based on an expanding feature modulation network—0
A Study of Efficient Light Field Subsampling and Reconstruction Strategies—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified