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 626–650 of 3874 papers

TitleStatusHype
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in ImagingCode1
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-ResolutionCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
DeFMO: Deblurring and Shape Recovery of Fast Moving ObjectsCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
Hierarchical Amortized Training for Memory-efficient High Resolution 3D GANCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional AutoencoderCode1
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution NetworksCode1
Improving Super-Resolution Performance using Meta-Attention LayersCode1
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image RescalingCode1
Cylin-Painting: Seamless 360 Panoramic Image Outpainting and BeyondCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
Compression-Aware Video Super-ResolutionCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-ResolutionCode1
Efficient Deep Models for Real-Time 4K Image Super-Resolution. NTIRE 2023 Benchmark and ReportCode1
Computing Multiple Image Reconstructions with a Single HypernetworkCode1
CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-ResolutionCode1
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image GenerationCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
Show:102550
← PrevPage 26 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified