Popular GitHub Repositories for Underwater

Fast underwater image enhancement for Improved Visual Perception. #TensorFlow #PyTorch #RAL2020

Kesci underwater object detection algorithm contest

Source code for UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing

Semantic Segmentation of Underwater Imagery: Dataset and Benchmark. #IROS2020

A CNN based image segmentation tool oriented to marine data analysis

Code and dataset for Single Underwater Image Restoration by Contrastive Learning, IGARSS 2021, oral.

Bayesian Neural Networks for One-to-Many Mapping in Image Enhancement

GAN-based fast underwater image enhancement.

A Residual and Attention-Driven Underwater Image Enhancement (UIE) method.

PyTorch implementation of the DICAM: Deep Inception and Channel-wise Attention Modules for underwater image enhancement

Implementation of paper 'Two Step Approach for Single Underwater Image Enhancement'

LocoMote: AI-driven Sensor Tags for Fine-Grained Undersea Localization and Sensing

Encoder-Residual-Decoder Underwater Image Enhancement with Frequency Detail Loss and Edge Detection Loss.

A Framework for Underwater Image Processing in Deep Learning.

underwater image enhancement and repair code.

An underwater image enhancement method and a corresponding image super-resolution algorithm. Image enhancement Technique. Super-resolution Convolutional neural networks the Retinex algorithm gamma correction. Dark prior

Detect crown-of-thorns starfish (COTS) in underwater image data based on YOLOv5 and Weighted Box Fusion (WBF). Kaggle: TensorFlow - Help Protect the Great Barrier Reef

YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).

[KBS 2025] SPMFormer: Simplified Physical Model-based Transformer with cross-space loss for Underwater Image Enhancement

Repository for the Project of Data Driven Machine Perception