Skip to content
master
Switch branches/tags
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 

TensorFlow and PyTorch implementations of the paper Fast Underwater Image Enhancement for Improved Visual Perception (RA-L 2020) and other GAN-based models.

funie-fig

Resources

Enhanced underwater imagery Improved detection and pose estimation
det-enh det-gif

FUnIE-GAN Features

  • Provides competitive performance for underwater image enhancement
  • Offers real-time inference on single-board computers
    • 48+ FPS on Jetson AGX Xavier, 25+ FPS on Jetson TX2
    • 148+ FPS on Nvidia GTX 1080
  • Suitable for underwater robotic deployments for enhanced vision

FUnIE-GAN Pointers

Underwater Image Enhancement: Recent Research and Resources

2019

Paper Theme Code Data
Multiscale Dense-GAN Residual multiscale dense block as generator
Fusion-GAN FGAN-based model, loss function formulation U45
UDAE U-Net denoising autoencoder
VDSR ResNet-based model, loss function formulation
JWCDN Joint wavelength compensation and dehazing
AWMD-Cycle-GAN Adaptive weighting for multi-discriminator training
WAug Encoder-Decoder Encoder-decoder module with wavelet pooling and unpooling GitHub
Water-Net Dataset and benchmark GitHub UIEB

2017-18

Paper Theme Code Data
UGAN Several GAN-based models, dataset formulation GitHub Uw-imagenet
Underwater-GAN Loss function formulation, cGAN-based model
LAB-MSR Multi-scale Retinex-based framework
Water-GAN Data generation from in-air image and depth pairings GitHub MHL, Field data
UIE-Net CNN-based model for color correction and haze removal

Non-deep Models

Reviews, Metrics, and Benchmarks

About

Fast underwater image enhancement for Improved Visual Perception. #TensorFlow #PyTorch

Topics

Resources

License

Releases

No releases published

Packages

No packages published

Languages