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 1031–1040 of 3874 papers

TitleStatusHype
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
Meta-SR: A Magnification-Arbitrary Network for Super-ResolutionCode1
How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale ApproachCode1
TDAN: Temporally Deformable Alignment Network for Video Super-ResolutionCode1
Learning Temporal Coherence via Self-Supervision for GAN-based Video GenerationCode1
Blockwise Parallel Decoding for Deep Autoregressive ModelsCode1
Lesion Focused Super-ResolutionCode1
Learning for Video Super-Resolution through HR Optical Flow EstimationCode1
The 2018 PIRM Challenge on Perceptual Image Super-resolutionCode1
The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified