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 1351–1400 of 3874 papers

TitleStatusHype
YOLO-MST: Multiscale deep learning method for infrared small target detection based on super-resolution and YOLO—0
TINQ: Temporal Inconsistency Guided Blind Video Quality AssessmentCode0
WaveDiffUR: A diffusion SDE-based solver for ultra magnification super-resolution in remote sensing images—0
Joint Multitarget Detection and Tracking with mmWave Radar—0
Foundation Model for Lossy Compression of Spatiotemporal Scientific Data—0
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution—0
Uncertainty Estimation for Super-Resolution using ESRGAN—0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Block-Based Multi-Scale Image Rescaling—0
Sequence Matters: Harnessing Video Models in 3D Super-Resolution—0
CLIP-SR: Collaborative Linguistic and Image Processing for Super-Resolution—0
EGP3D: Edge-guided Geometric Preserving 3D Point Cloud Super-resolution for RGB-D camera—0
Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model—0
A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport—0
Super-Resolution for Remote Sensing Imagery via the Coupling of a Variational Model and Deep Learning—0
SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolution—0
A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method—0
A Plug-and-Play Algorithm for 3D Video Super-Resolution of Single-Photon LiDAR data—0
Distribution free uncertainty quantification in neuroscience-inspired deep operators—0
FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements—0
Regional climate risk assessment from climate models using probabilistic machine learning—0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
RealOSR: Latent Unfolding Boosting Diffusion-based Real-world Omnidirectional Image Super-ResolutionCode0
MPSI: Mamba enhancement model for pixel-wise sequential interaction Image Super-Resolution—0
Hero-SR: One-Step Diffusion for Super-Resolution with Human Perception Priors—0
A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing—0
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery—0
You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors—0
Edge-SD-SR: Low Latency and Parameter Efficient On-device Super-Resolution with Stable Diffusion via Bidirectional Conditioning—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components—0
Unsupervised Hyperspectral and Multispectral Image Fusion via Self-Supervised Modality DecouplingCode0
MSECG: Incorporating Mamba for Robust and Efficient ECG Super-Resolution—0
Deep priors for satellite image restoration with accurate uncertainties—0
LocalSR: Image Super-Resolution in Local Region—0
2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts—0
LossAgent: Towards Any Optimization Objectives for Image Processing with LLM AgentsCode0
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image—0
Semantic Segmentation Prior for Diffusion-Based Real-World Super-Resolution—0
HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolution—0
MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range InteractionsCode0
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution—0
Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion ModelsCode0
FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution—0
HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion PriorCode0
HAAT: Hybrid Attention Aggregation Transformer for Image Super-Resolution—0
ΩSFormer: Dual-Modal Ω-like Super-Resolution Transformer Network for Cross-scale and High-accuracy Terraced Field Vectorization Extraction—0
Perceptually Optimized Super Resolution—0
From Diffusion to Resolution: Leveraging 2D Diffusion Models for 3D Super-Resolution Task—0
High-Resolution Be Aware! Improving the Self-Supervised Real-World Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified