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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1025 of 3874 papers

TitleStatusHype
Learning Light Field Angular Super-Resolution via a Geometry-Aware NetworkCode1
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
Fast Adaptation to Super-Resolution Networks via Meta-LearningCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI ScansCode1
HighRes-net: Multi-Frame Super-Resolution by Recursive FusionCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Scale-wise Convolution for Image RestorationCode1
Spatial-Angular Interaction for Light Field Image Super-ResolutionCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
High-dimensional Dense Residual Convolutional Neural Network for Light Field ReconstructionCode1
Lightweight Image Super-Resolution with Information Multi-distillation NetworkCode1
Underwater Image Super-Resolution using Deep Residual MultipliersCode1
TextSR: Content-Aware Text Super-Resolution Guided by RecognitionCode1
Learning Filter Basis for Convolutional Neural Network CompressionCode1
Learned Image Downscaling for Upscaling using Content Adaptive ResamplerCode1
Single Image Super-Resolution via CNN Architectures and TV-TV MinimizationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified