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 3641–3650 of 3874 papers

TitleStatusHype
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
Image Super-Resolution via Attention based Back Projection NetworksCode0
Image Super-Resolution Using Dense Skip ConnectionsCode0
DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRICode0
Image Super-Resolution Using a Wavelet-based Generative Adversarial NetworkCode0
"Zero-Shot" Super-Resolution using Deep Internal LearningCode0
Spherical Space Feature Decomposition for Guided Depth Map Super-ResolutionCode0
Data Upcycling Knowledge Distillation for Image Super-ResolutionCode0
Image Super-Resolution Improved by Edge InformationCode0
Image Super-Resolution by Neural Texture TransferCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified