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 3051–3060 of 3874 papers

TitleStatusHype
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-ResolutionCode0
SynFi: Automatic Synthetic Fingerprint GenerationCode1
Facial Attribute Capsules for Noise Face Super Resolution—0
Generator From Edges: Reconstruction of Facial Images—0
Video Face Super-Resolution with Motion-Adaptive Feedback Cell—0
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite ImageryCode1
Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution—0
EndoL2H: Deep Super-Resolution for Capsule EndoscopyCode1
Fast Generation of High Fidelity RGB-D Images by Deep-Learning with Adaptive ConvolutionCode1
Reconstructing the Noise Manifold for Image Denoising—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified