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 1601–1625 of 3874 papers

TitleStatusHype
Surveillance Face Anti-spoofing—0
In-situ monitoring additive manufacturing process with AI edge computing—0
Spectral Bandwidth Recovery of Optical Coherence Tomography Images using Deep Learning—0
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition—0
HSR-Diff: Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
Learning Correction Filter via Degradation-Adaptive Regression for Blind Single Image Super-ResolutionCode1
Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution—0
Fingerprinting Deep Image Restoration Models—0
Content-Aware Local GAN for Photo-Realistic Super-Resolution—0
Self-Supervised Burst Super-Resolution—0
Rethinking Multi-Contrast MRI Super-Resolution: Rectangle-Window Cross-Attention Transformer and Arbitrary-Scale UpsamplingCode1
EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction—0
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
Pyramid Dual Domain Injection Network for Pan-sharpening—0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Diffusion-Based Signed Distance Fields for 3D Shape Generation—0
Metadata-Based RAW Reconstruction via Implicit Neural Functions—0
Deep Random Projector: Accelerated Deep Image PriorCode1
Azimuth Super-Resolution for FMCW Radar in Autonomous DrivingCode1
Spatial-Frequency Mutual Learning for Face Super-ResolutionCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Memory-Friendly Scalable Super-Resolution via Rewinding Lottery Ticket Hypothesis—0
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified