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 1001–1010 of 3874 papers

TitleStatusHype
Unpaired Image Super-Resolution using Pseudo-SupervisionCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
PUGeo-Net: A Geometry-centric Network for 3D Point Cloud UpsamplingCode1
SynFi: Automatic Synthetic Fingerprint GenerationCode1
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite ImageryCode1
EndoL2H: Deep Super-Resolution for Capsule EndoscopyCode1
Fast Generation of High Fidelity RGB-D Images by Deep-Learning with Adaptive ConvolutionCode1
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual PerceptionCode1
Sound field reconstruction in rooms: inpainting meets super-resolutionCode1
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial NetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified