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 1151–1175 of 3874 papers

TitleStatusHype
Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and BenchmarkCode0
Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt—0
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution—0
StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation—0
Deep Learning Framework for Infrastructure Maintenance: Crack Detection and High-Resolution Imaging of Infrastructure Surfaces—0
A Fusion-Guided Inception Network for Hyperspectral Image Super-ResolutionCode0
Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks—0
USF Spectral Estimation: Prevalence of Gaussian Cramér-Rao Bounds Despite Modulo Folding—0
MSFNet-CPD: Multi-Scale Cross-Modal Fusion Network for Crop Pest DetectionCode0
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge—0
Unaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance—0
One Target, Many Views: Multi-User Fusion for Collaborative Uplink ISAC—0
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution—0
Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional NetworkCode0
Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution—0
SR-NeRV: Improving Embedding Efficiency of Neural Video Representation via Super-Resolution—0
FourierSpecNet: Neural Collision Operator Approximation Inspired by the Fourier Spectral Method for Solving the Boltzmann Equation—0
Super-resolution Wideband Beam Training for Near-field Communications with Ultra-low Overhead—0
Predicting Stress in Two-phase Random Materials and Super-Resolution Method for Stress Images by Embedding Physical Information—0
Global Stress Generation and Spatiotemporal Super-Resolution Physics-Informed Operator under Dynamic Loading for Two-Phase Random Materials—0
Geometry aware inference of steady state PDEs using Equivariant Neural Fields representationsCode0
CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors—0
Iterative Collaboration Network Guided By Reconstruction Prior for Medical Image Super-Resolution—0
Regularizing Differentiable Architecture Search with Smooth Activation—0
RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified