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 2701–2750 of 3874 papers

TitleStatusHype
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation—0
LAConv: Local Adaptive Convolution for Image Fusion—0
Compressed Ultrasound Imaging:from Sub-Nyquist Rates to Super-Resolution—0
High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss—0
RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank—0
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Level generation and style enhancement -- deep learning for game development overview—0
Multi-Attention Generative Adversarial Network for Remote Sensing Image Super-Resolution—0
Single-shot structured illumination microscopy—0
Learned super resolution ultrasound for improved breast lesion characterization—0
Image restoration quality assessment based on regional differential information entropy—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
Blind Image Super-Resolution: A Survey and Beyond—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
From General to Specific: Online Updating for Blind Super-Resolution—0
Impact of deep learning-based image super-resolution on binary signal detection—0
Can Super Resolution be used to improve Human Pose Estimation in Low Resolution Scenarios?—0
DeepCEL0 for 2D Single Molecule Localization in Fluorescence MicroscopyCode0
Blind Image Super-Resolution via Contrastive Representation Learning—0
IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representation—0
A Mixed-Supervision Multilevel GAN Framework for Image Quality Enhancement—0
"Zero-Shot" Point Cloud UpsamplingCode0
Advancing biological super-resolution microscopy through deep learning: a brief review—0
Video Super-Resolution with Long-Term Self-Exemplars—0
Distilling the Knowledge from Conditional Normalizing FlowsCode0
Applying VertexShuffle Toward 360-Degree Video Super-Resolution on Focused-Icosahedral-Mesh—0
Scene Text Telescope: Text-Focused Scene Image Super-ResolutionCode0
QPP: Real-Time Quantization Parameter Prediction for Deep Neural Networks—0
Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning—0
Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks—0
Light Field Super-Resolution With Zero-Shot Learning—0
Learning the Non-Differentiable Optimization for Blind Super-Resolution—0
Turning Frequency to Resolution: Video Super-Resolution via Event Cameras—0
Space-Time Distillation for Video Super-Resolution—0
MR Image Super-Resolution With Squeeze and Excitation Reasoning Attention Network—0
LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution—0
Data-Free Knowledge Distillation for Image Super-ResolutionCode0
Debiased Subjective Assessment of Real-World Image Enhancement—0
Leveraging Multi scale Backbone with Multilevel supervision for Thermal Image Super Resolution—0
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images—0
Perceptually-inspired super-resolution of compressed videos—0
Group-based Bi-Directional Recurrent Wavelet Neural Networks for Video Super-Resolution—0
Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution—0
Feedback Pyramid Attention Networks for Single Image Super-Resolution—0
A self-adapting super-resolution structures framework for automatic design of GAN—0
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified