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 1601–1650 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
Rethinking Multi-Contrast MRI Super-Resolution: Rectangle-Window Cross-Attention Transformer and Arbitrary-Scale UpsamplingCode1
HSR-Diff: Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
Fingerprinting Deep Image Restoration Models—0
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
MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition—0
Content-Aware Local GAN for Photo-Realistic Super-Resolution—0
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction—0
Self-Supervised Burst Super-Resolution—0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Pyramid Dual Domain Injection Network for Pan-sharpening—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
Toward Stable, Interpretable, and Lightweight Hyperspectral Super-ResolutionCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
Spectral Bayesian Uncertainty for Image Super-Resolution—0
Cross-Guided Optimization of Radiance Fields With Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis—0
Toward Accurate Post-Training Quantization for Image Super ResolutionCode0
Correspondence Transformers With Asymmetric Feature Learning and Matching Flow Super-ResolutionCode0
Memory-Friendly Scalable Super-Resolution via Rewinding Lottery Ticket Hypothesis—0
Spatial-Frequency Mutual Learning for Face Super-ResolutionCode1
RefSR-NeRF: Towards High Fidelity and Super Resolution View SynthesisCode0
AccelIR: Task-Aware Image Compression for Accelerating Neural Restoration—0
Rethinking Image Super Resolution From Long-Tailed Distribution Learning Perspective—0
Zero-Shot Dual-Lens Super-ResolutionCode1
Kernel Aware Resampler—0
Structure Aggregation for Cross-Spectral Stereo Image Guided DenoisingCode1
Compression-Aware Video Super-ResolutionCode1
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
One-Shot Model for Mixed-Precision Quantization—0
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration—0
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid NetworkCode0
Single-Image Super-Resolution Reconstruction based on the Differences of Neighboring Pixels—0
Large-scale single-photon imaging—0
Cross-Resolution Flow Propagation for Foveated Video Super-ResolutionCode1
Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-ResolutionCode1
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images—0
Infrared Image Super-Resolution: Systematic Review, and Future TrendsCode1
Continual Learning Approaches for Anomaly DetectionCode0
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified