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 2576–2600 of 3874 papers

TitleStatusHype
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling—0
MONAIfbs: MONAI-based fetal brain MRI deep learning segmentationCode1
A new public Alsat-2B dataset for single-image super-resolutionCode1
Hyperspectral Image Super-Resolution in Arbitrary Input-Output Band Settings—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Self-Supervised Adaptation for Video Super-ResolutionCode1
Prediction-assistant Frame Super-Resolution for Video Streaming—0
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation—0
Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar—0
Learning Frequency-aware Dynamic Network for Efficient Super-Resolution—0
Fast and Accurate: Video Enhancement using Sparse Depth—0
D2C-SR: A Divergence to Convergence Approach for Image Super-Resolution—0
A learning-based view extrapolation method for axial super-resolution—0
3D Human Pose, Shape and Texture from Low-Resolution Images and VideosCode1
Super-Resolving Beyond Satellite Hardware Using Realistically Degraded Images—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
Deep learning-based super-resolution fluorescence microscopy on small datasetsCode0
Feedback Refined Local-Global Network for Super-Resolution of Hyperspectral ImageryCode0
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data CharacteristicCode1
Generating Images with Sparse RepresentationsCode1
Super-resolution Method for Coherent DOA Estimation of Multiple Wideband Sources—0
Super-Resolution DOA Estimation for Wideband Signals using Arbitrary Linear Arrays without Focusing Matrices—0
Real-World Single Image Super-Resolution: A Brief ReviewCode1
Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution EnhancementCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified