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 911–920 of 3874 papers

TitleStatusHype
Solving Linear Inverse Problems Using the Prior Implicit in a DenoiserCode1
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised LearningCode1
MuCAN: Multi-Correspondence Aggregation Network for Video Super-ResolutionCode1
Frequency Domain-based Perceptual Loss for Super ResolutionCode1
Video Super-resolution with Temporal Group AttentionCode1
Face Super-Resolution Guided by 3D Facial PriorsCode1
Pyramid With Super Resolution for In-the-Wild Facial Expression RecognitionCode1
Event Enhanced High-Quality Image RecoveryCode1
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth ImagesCode1
Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image TranslationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified