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 3026–3050 of 3874 papers

TitleStatusHype
Hierarchical Neural Architecture Search for Single Image Super-ResolutionCode1
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds—0
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution—0
Perceptual Image Super-Resolution with Progressive Adversarial Network—0
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative ModelsCode3
Super Resolution Using Segmentation-Prior Self-Attention Generative Adversarial Network—0
Pixel-Level Self-Paced Learning for Super-ResolutionCode1
Weighted Encoding Based Image Interpolation With Nonlocal Linear Regression Model—0
Creating High Resolution Images with a Latent Adversarial GeneratorCode1
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge—0
Turbulence Enrichment using Physics-informed Generative Adversarial Networks—0
Residual learning based densely connected deep dilated network for joint deblocking and super resolution—0
MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better—0
Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players—0
Gated Fusion Network for Degraded Image Super ResolutionCode1
Joint Face Completion and Super-resolution using Multi-scale Feature Relation Learning—0
Meta-Transfer Learning for Zero-Shot Super-ResolutionCode1
Learning Light Field Angular Super-Resolution via a Geometry-Aware NetworkCode1
Super-Resolving Commercial Satellite Imagery Using Realistic Training Data—0
Unpaired Image Super-Resolution using Pseudo-SupervisionCode1
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-ResolutionCode1
RR-DnCNN v2.0: Enhanced Restoration-Reconstruction Deep Neural Network for Down-Sampling Based Video Coding—0
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
PUGeo-Net: A Geometry-centric Network for 3D Point Cloud UpsamplingCode1
3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified