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 351–375 of 3874 papers

TitleStatusHype
Conditional Variational Diffusion ModelsCode1
Spatial-Temporal Contrasting for Fine-Grained Urban Flow InferenceCode1
Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolutionCode1
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
PEAN: A Diffusion-Based Prior-Enhanced Attention Network for Scene Text Image Super-ResolutionCode1
Cross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-ResolutionCode1
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain ImagingCode1
Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion ModelsCode1
LFSRDiff: Light Field Image Super-Resolution via Diffusion ModelsCode1
Image Super-Resolution with Text Prompt DiffusionCode1
Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without NoiseCode1
Scene Text Image Super-resolution based on Text-conditional Diffusion ModelsCode1
A Spectral Diffusion Prior for Hyperspectral Image Super-ResolutionCode1
A Lightweight Recurrent Aggregation Network for Satellite Video Super-ResolutionCode1
Lightweight super resolution network for point cloud geometry compressionCode1
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic DataCode1
Optimal Transport-Guided Conditional Score-Based Diffusion ModelsCode1
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and ReconstructionCode1
INCODE: Implicit Neural Conditioning with Prior Knowledge EmbeddingsCode1
Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-ResolutionCode1
Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder ApproachCode1
Image super-resolution via dynamic networkCode1
ADASR: An Adversarial Auto-Augmentation Framework for Hyperspectral and Multispectral Data FusionCode1
Rethinking Dual-Stream Super-Resolution Semantic Learning in Medical Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified