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 921–930 of 3874 papers

TitleStatusHype
Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and ReconstructionCode1
Learned Compression for Images and Point CloudsCode1
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Bilateral Event Mining and Complementary for Event Stream Super-ResolutionCode1
Spatial-Angular Interaction for Light Field Image Super-ResolutionCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB ImageCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified