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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2376–2400 of 3874 papers

TitleStatusHype
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