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 1026–1050 of 3874 papers

TitleStatusHype
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain ConnectivityCode1
Efficient and Degradation-Adaptive Network for Real-World Image Super-ResolutionCode1
Enhanced Semantic Extraction and Guidance for UGC Image Super ResolutionCode1
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
Discrete Cosine Transform Network for Guided Depth Map Super-ResolutionCode1
Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great AgainCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
Dual Adversarial Adaptation for Cross-Device Real-World Image Super-ResolutionCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT CamerasCode1
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution NetworksCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and ResultsCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
Dual-Camera Super-Resolution with Aligned Attention ModulesCode1
NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator DiffusionCode1
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
Hypernetwork-Based Adaptive Image RestorationCode1
Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsCode1
Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image RepresentationCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
Ship in Sight: Diffusion Models for Ship-Image Super ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified