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 3421–3430 of 3874 papers

TitleStatusHype
Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal LearningCode0
MAMNet: Multi-path Adaptive Modulation Network for Image Super-ResolutionCode0
Image Reconstruction with Predictive Filter FlowCode0
Dense xUnit NetworksCode0
Patch-based Progressive 3D Point Set UpsamplingCode0
Deep Laplacian Pyramid Network for Text Images Super-ResolutionCode0
Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images—0
Learning Temporal Coherence via Self-Supervision for GAN-based Video GenerationCode1
NeuroTreeNet: A New Method to Explore Horizontal Expansion Network—0
IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified