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 2351–2400 of 3874 papers

TitleStatusHype
Multi-BVOC Super-Resolution Exploiting Compounds Inter-Connection—0
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results—0
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution—0
Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems—0
Multi-Contrast Super-Resolution MRI Through a Progressive Network—0
Computational structured illumination for high-content fluorescent and phase microscopy—0
Multi-dimensional topological loss for cortical plate segmentation in fetal brain MRI—0
Computational resolution limit: a theory towards super-resolution—0
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network—0
SGSR: Structure-Guided Multi-Contrast MRI Super-Resolution via Spatio-Frequency Co-Query Attention—0
Multi-Field De-interlacing using Deformable Convolution Residual Blocks and Self-Attention—0
Multi-frame image super-resolution with fast upscaling technique—0
Triple Attention Mixed Link Network for Single Image Super Resolution—0
Multi-Frame Super-Resolution Combining Demons Registration and Regularized Bayesian Reconstruction—0
Multi-frame Super-resolution from Noisy Data—0
Multi-Frame Super-Resolution Reconstruction with Applications to Medical Imaging—0
Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution—0
Multi-grained Attention Networks for Single Image Super-Resolution—0
Multi-granularity Backprojection Transformer for Remote Sensing Image Super-Resolution—0
A Comparative Study on 1.5T-3T MRI Conversion through Deep Neural Network Models—0
Compressive Holographic Video—0
Compressing GANs using Knowledge Distillation—0
Multi-image Super-resolution via Quality Map Associated Attention Network—0
Suppressing Model Overfitting for Image Super-Resolution Networks—0
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution—0
Multi-level Encoder-Decoder Architectures for Image Restoration—0
Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution—0
Trustworthy modelling of atmospheric formaldehyde powered by deep learning—0
Trustworthy SR: Resolving Ambiguity in Image Super-resolution via Diffusion Models and Human Feedback—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
Multimodal-Boost: Multimodal Medical Image Super-Resolution using Multi-Attention Network with Wavelet Transform—0
Multi-modal Datasets for Super-resolution—0
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing—0
Multimodal Deep Unfolding for Guided Image Super-Resolution—0
Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild—0
Multi-modal Image Processing based on Coupled Dictionary Learning—0
Multimodal Image Super-resolution via Deep Unfolding with Side Information—0
TSP-Mamba: The Travelling Salesman Problem Meets Mamba for Image Super-resolution and Beyond—0
Compressing Deep Image Super-resolution Models—0
A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution—0
Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database—0
Compressed Video Super-Resolution based on Hierarchical Encoding—0
A Comparative Study of Feature Expansion Unit for 3D Point Cloud Upsampling—0
Multi-Modal Super Resolution for Dense Microscopic Particle Size Estimation—0
A comparative analysis of SRGAN models—0
Multiple Angles of Arrival Estimation using Neural Networks—0
Multiple Exemplars-based Hallucinationfor Face Super-resolution and Editing—0
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach—0
Turbulence Enrichment using Physics-informed Generative Adversarial Networks—0
Multi-resolution Data Fusion for Super-Resolution Electron Microscopy—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified