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 501–525 of 3874 papers

TitleStatusHype
Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-ResolutionCode1
Hyperspectral Image Super Resolution with Real Unaligned RGB GuidanceCode1
Towards Geospatial Foundation Models via Continual PretrainingCode1
Hypernetworks build Implicit Neural Representations of SoundsCode1
OSRT: Omnidirectional Image Super-Resolution with Distortion-aware TransformerCode1
Accelerating Guided Diffusion Sampling with Splitting Numerical MethodsCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
Learning Continuous Mesh Representation with Spherical Implicit SurfaceCode1
WIRE: Wavelet Implicit Neural RepresentationsCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
Structure Aggregation for Cross-Spectral Stereo Image Guided DenoisingCode1
Compression-Aware Video Super-ResolutionCode1
Zero-Shot Dual-Lens Super-ResolutionCode1
Rethinking Multi-Contrast MRI Super-Resolution: Rectangle-Window Cross-Attention Transformer and Arbitrary-Scale UpsamplingCode1
Azimuth Super-Resolution for FMCW Radar in Autonomous DrivingCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
Toward Stable, Interpretable, and Lightweight Hyperspectral Super-ResolutionCode1
Spatial-Frequency Mutual Learning for Face Super-ResolutionCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
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
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified