DeepAI AI Chat
Log In Sign Up

UDD: An Underwater Open-sea Farm Object Detection Dataset for Underwater Robot Picking

by   Zhihui Wang, et al.
Dalian University of Technology

To promote the development of underwater robot picking in sea farms, we propose an underwater open-sea farm object detection dataset called UDD. Concretely, UDD consists of 3 categories (seacucumber, seaurchin, and scallop) with 2227 images. To the best of our knowledge, it's the first dataset collected in a real open-sea farm for underwater robot picking and we also propose a novel Poisson-blending-embedded Generative Adversarial Network (Poisson GAN) to overcome the class-imbalance and massive small objects issues in UDD. By utilizing Poisson GAN to change the number, position, even size of objects in UDD, we construct a large scale augmented dataset (AUDD) containing 18K images. Besides, in order to make the detector better adapted to the underwater picking environment, a dataset (Pre-trained dataset) for pre-training containing 590K images is also proposed. Finally, we design a lightweight network (UnderwaterNet) to address the problems that detecting small objects from cloudy underwater pictures and meeting the efficiency requirements in robots. Specifically, we design a depth-wise-convolution-based Multi-scale Contextual Features Fusion (MFF) block and a Multi-scale Blursampling (MBP) module to reduce the parameters of the network to 1.3M at 48FPS, without any loss on accuracy. Extensive experiments verify the effectiveness of the proposed UnderwaterNet, Poisson GAN, UDD, AUDD, and Pre-trained datasets.


page 1

page 3

page 4

page 6

page 8

page 9


Underwater object detection using Invert Multi-Class Adaboost with deep learning

In recent years, deep learning based methods have achieved promising per...

A Generative Approach for Detection-driven Underwater Image Enhancement

In this paper, we introduce a generative model for image enhancement spe...

Edge-guided Representation Learning for Underwater Object Detection

Underwater object detection (UOD) is crucial for marine economic develop...

MLFcGAN: Multi-level Feature Fusion based Conditional GAN for Underwater Image Color Correction

Color correction for underwater images has received increasing interests...

SWIPENET: Object detection in noisy underwater images

In recent years, deep learning based object detection methods have achie...

A Dataset And Benchmark Of Underwater Object Detection For Robot Picking

Underwater object detection for robot picking has attracted a lot of int...

A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis

Visual analysis of complex fish habitats is an important step towards su...