---
title: SQUID
canonical_url: "https://www.modelscope.cn/datasets/OpenDataLab/SQUID"
md_url: "https://www.modelscope.cn/datasets/OpenDataLab/SQUID.md"
repository: OpenDataLab/SQUID
last_updated: 2024-07-15
license: "[Unknown]"
storage_size: "33 GB"
domain:
  - publishDate
  - publishUrl
  - paperUrl
  - taskTypes
  - displayName
  - publisher
tasks:
  - 2019
  - "http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/index.html"
  - "https://arxiv.org/pdf/1811.01343v3.pdf"
  - "Image Enhancement"
  - "SQUID (Stereo Quantitative Underwater Image Dataset)"
  - "University of Haifa"
downloads: 1259
stars: 0
---

# SQUID

> SQUID - OpenDataLab 在 ModelScope 开源的数据集。displayName: SQUID (Stereo Quantitative Underwater Image Dataset) license: Unknown paperUrl: https://arxiv.org/pdf/1811.01343v3.pdf publishDate: "2019" publishUrl:…

OpenDataLab/SQUID 是 ModelScope 魔搭社区上的2019、http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/index.html、https://arxiv.org/pdf/1811.01343v3.pdf数据集，涉及 publishDate、publishUrl、paperUrl 领域，存储大小 33 GB，采用 [Unknown] 许可。

- **Repository**: OpenDataLab/SQUID
- **License**: [Unknown]
- **Tasks**: 2019, http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/index.html, https://arxiv.org/pdf/1811.01343v3.pdf, Image Enhancement, SQUID (Stereo Quantitative Underwater Image Dataset), University of Haifa
- **Domain**: publishDate, publishUrl, paperUrl, taskTypes, displayName, publisher
- **Storage size**: 33 GB
- **Downloads**: 1259
- **Stars**: 0
- **Last updated**: 2024-07-15

Source: https://www.modelscope.cn/datasets/OpenDataLab/SQUID

---

displayName: SQUID (Stereo Quantitative Underwater Image Dataset)
license:
- Unknown
paperUrl: https://arxiv.org/pdf/1811.01343v3.pdf
publishDate: "2019"
publishUrl: http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/index.html
publisher:
- Tel Aviv University
- University of Haifa
tags:
- Underwater Image
taskTypes:
- Image Dehazing
- Single Image Dehazing
- Image Enhancement

---
# 数据集介绍
  ## 简介
  在不同位置拍摄的具有不同水特性的图像数据集，显示场景中的彩色图表。此外，为了获得地面真相，基于立体成像计算了场景的3D结构。此数据集可以定量评估自然图像上的恢复算法。
  ## 引文
  ```
@article{berman2020underwater,
  title={Underwater single image color restoration using haze-lines and a new quantitative dataset},
  author={Berman, Dana and Levy, Deborah and Avidan, Shai and Treibitz, Tali},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={43},
  number={8},
  pages={2822--2837},
  year={2020},
  publisher={IEEE}
}
```
  
## Download dataset
:modelscope-code[]{type="git"}