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 3401–3425 of 3874 papers

TitleStatusHype
Deep Hyperspectral Prior: Denoising, Inpainting, Super-ResolutionCode0
Deep Generative Model based Rate-Distortion for Image Downscaling AssessmentCode0
Efficient Model-Based Deep Learning via Network Pruning and Fine-TuningCode0
MetH: A family of high-resolution and variable-shape image challengesCode0
Efficient Residual Dense Block Search for Image Super-ResolutionCode0
Super-resolution of Omnidirectional Images Using Adversarial LearningCode0
Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral ImagesCode0
ASteISR: Adapting Single Image Super-resolution Pre-trained Model for Efficient Stereo Image Super-resolutionCode0
Toward Real-World Light Field Super-ResolutionCode0
Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labelsCode0
Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural networkCode0
Efficient Meta-Tuning for Content-aware Neural Video DeliveryCode0
MemNet: A Persistent Memory Network for Image RestorationCode0
A Self-Supervised Deep Denoiser for Hyperspectral and Multispectral Image FusionCode0
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and EnhancementCode0
Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image InformationCode0
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR ImagesCode0
OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-ResolutionCode0
Wide Activation for Efficient and Accurate Image Super-ResolutionCode0
Efficient Light Field Reconstruction via Spatio-Angular Dense NetworkCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
Medical Image Imputation from Image CollectionsCode0
Palantir: Towards Efficient Super Resolution for Ultra-high-definition Live StreamingCode0
Maximum Likelihood on the Joint (Data, Condition) Distribution for Solving Ill-Posed Problems with Conditional Flow ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified