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

Showing 201210 of 3874 papers

TitleStatusHype
ICME 2025 Grand Challenge on Video Super-Resolution for Video ConferencingCode1
Structural Similarity-Inspired Unfolding for Lightweight Image Super-ResolutionCode1
A Tree-guided CNN for image super-resolutionCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
Semantic-Guided Diffusion Model for Single-Step Image Super-ResolutionCode1
EvEnhancer: Empowering Effectiveness, Efficiency and Generalizability for Continuous Space-Time Video Super-Resolution with EventsCode1
Small Clips, Big Gains: Learning Long-Range Refocused Temporal Information for Video Super-ResolutionCode1
Survey of Video Diffusion Models: Foundations, Implementations, and ApplicationsCode1
SupResDiffGAN a new approach for the Super-Resolution taskCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified