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 1351–1360 of 3874 papers

TitleStatusHype
SR+Codec: a Benchmark of Super-Resolution for Video Compression Bitrate ReductionCode0
Learning Accurate and Enriched Features for Stereo Image Super-ResolutionCode0
Learning a No-Reference Quality Metric for Single-Image Super-ResolutionCode0
Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution ImagingCode0
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-ResolutionCode0
LD-GAN: Low-Dimensional Generative Adversarial Network for Spectral Image Generation with Variance RegularizationCode0
Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in NetworkCode0
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid NetworksCode0
Ensemble Super-Resolution with A Reference DatasetCode0
LAR-SR: A Local Autoregressive Model for Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified