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 2921–2930 of 3874 papers

TitleStatusHype
Joint Demosaicing and Denoising With Self GuidanceCode1
TDAN: Temporally-Deformable Alignment Network for Video Super-ResolutionCode1
Residual Feature Aggregation Network for Image Super-Resolution—0
Dual Super-Resolution Learning for Semantic SegmentationCode1
Inter-Task Association Critic for Cross-Resolution Person Re-Identification—0
Deep super resolution crack network (SrcNet) for improving computer vision–based automated crack detectability in in situ bridges—0
Hyperspectral Image Super-resolution via Deep Spatio-spectral Convolutional Neural Networks—0
Zoom in to the details of human-centric videos—0
Perceptual Extreme Super Resolution Network with Receptive Field BlockCode1
Bayesian Conditional GAN for MRI Brain Image Synthesis—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified