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 326–350 of 3874 papers

TitleStatusHype
Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRICode1
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution NetworksCode1
A Spectral Diffusion Prior for Hyperspectral Image Super-ResolutionCode1
Collaborative Feedback Discriminative Propagation for Video Super-ResolutionCode1
Does Diffusion Beat GAN in Image Super Resolution?Code1
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-ResolutionCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-ResolutionCode1
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data CharacteristicCode1
DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRFCode1
ControlSR: Taming Diffusion Models for Consistent Real-World Image Super ResolutionCode1
Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great AgainCode1
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution NetworksCode1
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image SynthesisCode1
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection StrategyCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Closed-loop Matters: Dual Regression Networks for Single Image Super-ResolutionCode1
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-ResolutionCode1
Combining Attention Module and Pixel Shuffle for License Plate Super-ResolutionCode1
Discrete Cosine Transform Network for Guided Depth Map Super-ResolutionCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
DL4DS -- Deep Learning for empirical DownScalingCode1
DSR: Towards Drone Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified