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 681–690 of 3874 papers

TitleStatusHype
Learning Filter Basis for Convolutional Neural Network CompressionCode1
DynaVSR: Dynamic Adaptive Blind Video Super-ResolutionCode1
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth ImagesCode1
Human Guided Ground-truth Generation for Realistic Image Super-resolutionCode1
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-trainingCode1
EBSR: Feature Enhanced Burst Super-Resolution With Deformable AlignmentCode1
Hybrid Pixel-Unshuffled Network for Lightweight Image Super-ResolutionCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
edge-SR: Super-Resolution For The MassesCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified