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 1091–1100 of 3874 papers

TitleStatusHype
Multi Kernel Estimation based Object SegmentationCode0
Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled DictionariesCode0
Detecting Overfitting of Deep Generative Networks via Latent RecoveryCode0
Detail-revealing Deep Video Super-resolutionCode0
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
Multiframe Motion Coupling for Video Super ResolutionCode0
Multigrid Backprojection Super-Resolution and Deep Filter VisualizationCode0
Depth Super-Resolution Meets Uncalibrated Photometric StereoCode0
Blind Image Fusion for Hyperspectral Imaging with the Directional Total VariationCode0
Multi-Modality Image Super-Resolution using Generative Adversarial NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified