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 2871–2880 of 3874 papers

TitleStatusHype
PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration—0
An Image Analogies Approach for Multi-Scale Contour Detection—0
Video Super-resolution with Temporal Group AttentionCode1
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution—0
Face Super-Resolution Guided by 3D Facial PriorsCode1
Pyramid With Super Resolution for In-the-Wild Facial Expression RecognitionCode1
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth ImagesCode1
Super-Resolution Remote Imaging using Time Encoded Remote Apertures—0
Event Enhanced High-Quality Image RecoveryCode1
Learning with Privileged Information for Efficient Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified