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 1161–1170 of 3874 papers

TitleStatusHype
Deep learning-based image super-resolution of a novel end-expandable optical fiber probe for application in esophageal cancer diagnostics—0
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution—0
A Restoration Network as an Implicit Prior—0
RF-ULM: Ultrasound Localization Microscopy Learned from Radio-Frequency WavefrontsCode1
Forecasting Tropical Cyclones with Cascaded Diffusion ModelsCode1
CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems—0
A New Real-World Video Dataset for the Comparison of Defogging Algorithms—0
EXTRACTER: Efficient Texture Matching with Attention and Gradient Enhancing for Large Scale Image Super ResolutionCode0
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
Prompt-tuning latent diffusion models for inverse problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified