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 1381–1390 of 3874 papers

TitleStatusHype
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
MSECG: Incorporating Mamba for Robust and Efficient ECG Super-Resolution—0
Unsupervised Hyperspectral and Multispectral Image Fusion via Self-Supervised Modality DecouplingCode0
Deep priors for satellite image restoration with accurate uncertainties—0
2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts—0
LocalSR: Image Super-Resolution in Local Region—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
MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range InteractionsCode0
HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified