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 1001–1025 of 3874 papers

TitleStatusHype
CDFormer: When Degradation Prediction Embraces Diffusion Model for Blind Image Super-ResolutionCode2
Beyond Subspace Isolation: Many-to-Many Transformer for Light Field Image Super-resolutionCode0
Diffusion Models, Image Super-Resolution And Everything: A Survey—0
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
UGPNet: Universal Generative Prior for Image Restoration—0
Compressing Deep Image Super-resolution Models—0
Image Super-resolution Reconstruction Network based on Enhanced Swin Transformer via Alternating Aggregation of Local-Global Features—0
Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-ResolutionCode2
Noise-free Optimization in Early Training Steps for Image Super-ResolutionCode1
Single particle algorithms to reveal cellular nanodomain organization—0
KeDuSR: Real-World Dual-Lens Super-Resolution via Kernel-Free MatchingCode1
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction—0
A Survey on Super Resolution for video Enhancement Using GAN—0
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—0
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned GuidanceCode1
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization PerspectiveCode1
BSRAW: Improving Blind RAW Image Super-Resolution—0
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
Super-resolution of THz time-domain images based on low-rank representation—0
A Comprehensive End-to-End Computer Vision Framework for Restoration and Recognition of Low-Quality Engineering DrawingsCode0
HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion ModelsCode2
EPNet: An Efficient Pyramid Network for Enhanced Single-Image Super-Resolution with Reduced Computational Requirements—0
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-trainingCode1
Learning Exhaustive Correlation for Spectral Super-Resolution: Where Spatial-Spectral Attention Meets Linear Dependence—0
How Good Are Deep Generative Models for Solving Inverse Problems?—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified