Underwater Image Restoration
14 papers with code • 1 benchmarks • 2 datasets
Underwater image restoration aims to rectify the distorted colors and present the true colors of the underwater scene.
Benchmarks
These leaderboards are used to track progress in Underwater Image Restoration
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
LSUI
MVK
Most implemented papers
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
As a result, our network can effectively improve the visual quality of underwater images by exploiting multiple color spaces embedding and the advantages of both physical model-based and learning-based methods.
Enhancing Underwater Imagery using Generative Adversarial Networks
cameronfabbri/Underwater-Color-Correction
•
•
Autonomous underwater vehicles (AUVs) rely on a variety of sensors - acoustic, inertial and visual - for intelligent decision making.
Fast Underwater Image Enhancement for Improved Visual Perception
In this paper, we present a conditional generative adversarial network-based model for real-time underwater image enhancement.
U-shape Transformer for Underwater Image Enhancement
LintaoPeng/U-shape_Transformer
•
•
In this work, we constructed a large-scale underwater image (LSUI) dataset including 5004 image pairs, and reported an U-shape Transformer network where the transformer model is for the first time introduced to the UIE task.
An Underwater Image Enhancement Benchmark Dataset and Beyond
tnwei/waternet
•
•
In this paper, we construct an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images.
Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations
Surprisingly, we demonstrate that PEOF is more efficient and often outperforms all the state of the art methods in terms of numerical measures.
Single Underwater Image Restoration by Contrastive Learning
JunlinHan/CWR
•
•
Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world.
Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration
pksvision/Deep-WaveNet-Underwater-Image-Restoration
•
•
Background: Underwater images, in general, suffer from low contrast and high color distortions due to the non-uniform attenuation of the light as it propagates through the water.
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
JunlinHan/CWR
•
•
There are 2000 reference restored images and 6003 original underwater images in the unpaired training set.
MetaUE: Model-based Meta-learning for Underwater Image Enhancement
The meta-learning strategy is used to obtain a pre-trained model on the synthetic underwater dataset, which contains different types of degradation to cover the various underwater environments.
