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 3076–3100 of 3874 papers

TitleStatusHype
Monte-Carlo Siamese Policy on Actor for Satellite Image Super Resolution—0
Time accelerated image super-resolution using shallow residual feature representative network—0
Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes—0
Deep Attentive Generative Adversarial Network for Photo-Realistic Image De-Quantization—0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces—0
Feature-Driven Super-Resolution for Object Detection—0
When to Use Convolutional Neural Networks for Inverse Problems—0
Super Resolution for Root ImagingCode0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Reducing Magnetic Resonance Image Spacing by Learning Without Ground-Truth—0
Learning regularization and intensity-gradient-based fidelity for single image super resolution—0
Across-scale Process Similarity based Interpolation for Image Super-Resolution—0
Towards a Computer Vision Particle Flow—0
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention—0
Weak Texture Information Map Guided Image Super-resolution with Deep Residual Networks—0
Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?—0
Pyramidal Edge-maps and Attention based Guided Thermal Super-resolution—0
Memory-efficient Learning for Large-scale Computational Imaging—0
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution—0
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds—0
Perceptual Image Super-Resolution with Progressive Adversarial Network—0
Super Resolution Using Segmentation-Prior Self-Attention Generative Adversarial Network—0
Turbulence Enrichment using Physics-informed Generative Adversarial Networks—0
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified