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 1201–1225 of 3874 papers

TitleStatusHype
Deterministic Medical Image Translation via High-fidelity Brownian Bridges—0
RELD: Regularization by Latent Diffusion Models for Image Restoration—0
Evaluation of Machine-generated Biomedical Images via A Tally-based Similarity Measure—0
Knowledge Rectification for Camouflaged Object Detection: Unlocking Insights from Low-Quality Data—0
Diffusion Image Prior—0
Residual Learning Inspired Crossover Operator and Strategy Enhancements for Evolutionary Multitasking—0
PLAIN: Scalable Estimation Architecture for Integrated Sensing and CommunicationCode0
Simulation-informed deep learning for enhanced SWOT observations of fine-scale ocean dynamics—0
KernelFusion: Assumption-Free Blind Super-Resolution via Patch Diffusion—0
Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications—0
ESSR: An 8K@30FPS Super-Resolution Accelerator With Edge Selective Network—0
Consistency Trajectory Matching for One-Step Generative Super-Resolution—0
Single-Step Latent Consistency Model for Remote Sensing Image Super-Resolution—0
L^2FMamba: Lightweight Light Field Image Super-Resolution with State Space Model—0
Burst Image Super-Resolution with Mamba—0
Leveraging Land Cover Priors for Isoprene Emission Super-Resolution—0
Benchmarking Burst Super-Resolution for Polarization Images: Noise Dataset and Analysis—0
Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model—0
A Two-Stage Rotation-Based Super-Resolution Signature Estimation for Spatial Wideband Systems—0
Hierarchy-Aware and Channel-Adaptive Semantic Communication for Bandwidth-Limited Data Fusion—0
Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration—0
Anatomically Guided Motion Correction for Placental IVIM Parameter Estimation with Accelerated Sampling Method—0
R2LDM: An Efficient 4D Radar Super-Resolution Framework Leveraging Diffusion Model—0
PH2ST:ST-Prompt Guided Histological Hypergraph Learning for Spatial Gene Expression Prediction—0
DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified