https://github.com/PeiqinZhuang/WildFish

WildFish: A Large Benchmark for Fish Recognition in the Wild
https://github.com/PeiqinZhuang/WildFish

fish fish-dataset fish-recognition underwater

Last synced: 23 days ago
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WildFish: A Large Benchmark for Fish Recognition in the Wild

• Host: GitHub
• URL: https://github.com/PeiqinZhuang/WildFish
• Owner: PeiqinZhuang
• Created: 2018-11-12T11:36:07.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2024-04-29T22:43:59.000Z (over 1 year ago)
• Last Synced: 2024-05-14T02:10:15.779Z (over 1 year ago)
• Topics: fish, fish-dataset, fish-recognition, underwater
• Homepage:
• Size: 9.76 MB
• Stars: 55
• Watchers: 2
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• Awesome_Underwater_Datasets - Data

README

          
![image](/paper/WildFish_cover.jpg)

# Introduction:

In this project, we collect a large scale benchmark named WildFish for fish recognition in the wild. To our best knowledge, it is the largest fish dataset compared with existing fish datasets. It consists of **1,000 fish categories** with **54,459 unconstraint images**, enabling the training of high-capacity models for automatic fish classification. In addition, we also propose some novel open-set classification exploration practices and leverage pairwise textual descriptions to distinguish highly-confused species based on some realistic scenarios. More details can be found in our [paper](https://dl.acm.org/citation.cfm?id=3240616).

# News:

- Please reach me at zpq0316@163.com, if you have difficulties when using BaiduYun to download the dataset.

- Nov. 12, 2018 We officially release WildFish_version1, which was used in our ACM-MM paper.

# Tasks:

## 1. Open-Set Fish Classification:

![image](/paper/OpenSet_Framework.png)

## 2. Fine-grained Fish Recognition with Pairwise Text Descriptions

![image](/paper/pairwise.png)

# Download:

WildFish dataset can be downloaded from [[BaiduYun](https://pan.baidu.com/s/1tBO3EiWi-zHFfELsyjNbXA?pwd=01km)]. All the settings in our paper can be found in the zip file.

# Citing:

Please kindly cite the following paper, if you use WildFish in your work.

```

@inproceedings{zhuang2018wildfish,

  title={WildFish: A Large Benchmark for Fish Recognition in the Wild},

  author={Zhuang, Peiqin and Wang, Yali and Qiao, Yu},

  booktitle={2018 ACM Multimedia Conference on Multimedia Conference},

  pages={1301--1309},

  year={2018},

  organization={ACM}

}

```

# Contact:

Please feel free to contact zpq0316@163.com, if you have any questions about WildFish.