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 851–875 of 3874 papers

TitleStatusHype
Learning Graph Regularisation for Guided Super-ResolutionCode1
Learning Large-Factor EM Image Super-Resolution with Generative PriorsCode1
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural NetworksCode1
DeFMO: Deblurring and Shape Recovery of Fast Moving ObjectsCode1
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable AlignmentCode1
Learning Light Field Angular Super-Resolution via a Geometry-Aware NetworkCode1
Image Super-Resolution Using Deep Convolutional NetworksCode1
Image super-resolution via dynamic networkCode1
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS DataCode1
Rethinking Dual-Stream Super-Resolution Semantic Learning in Medical Image SegmentationCode1
Rethinking Multi-Contrast MRI Super-Resolution: Rectangle-Window Cross-Attention Transformer and Arbitrary-Scale UpsamplingCode1
Rethinking the modeling of the instrumental response of telescopes with a differentiable optical modelCode1
Bayesian Image Reconstruction using Deep Generative ModelsCode1
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolutionCode1
Bayesian Image Super-Resolution with Deep Modeling of Image StatisticsCode1
Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder ApproachCode1
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars MiningCode1
Image Super-resolution with An Enhanced Group Convolutional Neural NetworkCode1
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-ResolutionCode1
Image Super-Resolution with Deep DictionaryCode1
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
Accelerating Diffusion Models for Inverse Problems through Shortcut SamplingCode1
Learning Mutual Modulation for Self-Supervised Cross-Modal Super-ResolutionCode1
Learning Spatial Attention for Face Super-ResolutionCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified