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

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Showing 401–425 of 3874 papers

TitleStatusHype
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and ReconstructionCode1
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion ModelCode1
Deep Blind Video Super-resolutionCode1
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image DenoisingCode1
AutoGAN-Distiller: Searching to Compress Generative Adversarial NetworksCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
EndoL2H: Deep Super-Resolution for Capsule EndoscopyCode1
Automatic quality control in multi-centric fetal brain MRI super-resolution reconstructionCode1
End-to-end Alternating Optimization for Real-World Blind Super ResolutionCode1
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-ResolutionCode1
BF-STVSR: B-Splines and Fourier---Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Enhanced Hyperspectral Image Super-Resolution via RGB Fusion and TV-TV MinimizationCode1
Enhanced Semantic Extraction and Guidance for UGC Image Super ResolutionCode1
Enhanced Super-Resolution Training via Mimicked Alignment for Real-World ScenesCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Deep Burst Super-ResolutionCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder ArchitectureCode1
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolutionCode1
BAM: A Balanced Attention Mechanism for Single Image Super ResolutionCode1
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB ImageCode1
Edge and Identity Preserving Network for Face Super-ResolutionCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified