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 2411–2420 of 3874 papers

TitleStatusHype
Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation—0
Multi-Step Guided Diffusion for Image Restoration on Edge Devices: Toward Lightweight Perception in Embodied AI—0
Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network—0
Hypernetwork functional image representation—0
Multitask Learning for VVC Quality Enhancement and Super-Resolution—0
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution—0
Multi-Texture GAN: Exploring the Multi-Scale Texture Translation for Brain MR Images—0
Multi-View Dynamic Shape Refinement Using Local Temporal Integration—0
Two-dimensional gridless super-resolution method for ISAR imaging—0
Two-phase Hair Image Synthesis by Self-Enhancing Generative Model—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified