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 1211–1220 of 3874 papers

TitleStatusHype
ESSR: An 8K@30FPS Super-Resolution Accelerator With Edge Selective Network—0
Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications—0
L^2FMamba: Lightweight Light Field Image Super-Resolution with State Space Model—0
Single-Step Latent Consistency Model for Remote Sensing Image Super-Resolution—0
Burst Image Super-Resolution with Mamba—0
Benchmarking Burst Super-Resolution for Polarization Images: Noise Dataset and Analysis—0
Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model—0
Leveraging Land Cover Priors for Isoprene Emission Super-Resolution—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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified