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xahidbuffon
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Description

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

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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

  • Paper: https://ieeexplore.ieee.org/document/9001231
  • Preprint: https://arxiv.org/pdf/1903.09766.pdf
  • Datasets: http://irvlab.cs.umn.edu/resources/euvp-dataset
  • Bibliography entry for citation:
    @article{islam2019fast,
        title={Fast Underwater Image Enhancement for Improved Visual Perception},
        author={Islam, Md Jahidul and Xia, Youya and Sattar, Junaed},
        journal={IEEE Robotics and Automation Letters (RA-L)},
        volume={5},
        number={2},
        pages={3227--3234},
        year={2020},
        publisher={IEEE}
    }
    

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

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