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 1541–1550 of 3874 papers

TitleStatusHype
SRECG: ECG Signal Super-resolution Framework for Portable/Wearable Devices in Cardiac Arrhythmias ClassificationCode0
Image Super-Resolution Using Dense Skip ConnectionsCode0
Image Super-Resolution as a Defense Against Adversarial AttacksCode0
Image Super-Resolution by Neural Texture TransferCode0
EarthGen: Generating the World from Top-Down ViewsCode0
Image Super-Resolution Improved by Edge InformationCode0
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip ConnectionsCode0
Image Restoration Using Deep Regulated Convolutional NetworksCode0
E2FIF: Push the limit of Binarized Deep Imagery Super-resolution using End-to-end Full-precision Information FlowCode0
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip ConnectionsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified