---
license: apache-2.0
task_categories:
- image-segmentation
language:
- en
tags:
- panorama
pretty_name: WildPASS
size_categories:
- 100M<n<1B
---

<div align="center" style="display: flex; align-items: center; justify-content: center; gap: 16px;">
  <div style="text-align: center;">
    <h1 style="margin: 0; font-size: 2em;">WildPASS Dataset</h1>
    <p style="margin: 6px 0 0; font-size: 1.2em;">A panoramic dataset for outdoor semantic segmentation</p>
  </div>
</div>

## 📕 Introduction

This dataset originates from [WildPASS](https://github.com/elnino9ykl/WildPASS) and is used by our ECCV'24 paper [OPS](https://junweizheng93.github.io/publications/OPS/OPS.html).

If you're interested in my research topics, feel free to check [my homepage](https://junweizheng93.github.io/) for more findings!

If you're interested in this dataset, please cite the following papers:

## 📖 Citation
```text
@inproceedings{yang2021capturing,
title={Capturing Omni-Range Context for Omnidirectional Segmentation},
author={Yang, Kailun and Zhang, Jiaming and Rei{\ss}, Simon and Hu, Xinxin and Stiefelhagen, Rainer},
booktitle={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2021}
}
```
```text
@article{yang2021context,
title={Is Context-Aware CNN Ready for the Surroundings? Panoramic Semantic Segmentation in the Wild},
author={Yang, Kailun and Hu, Xinxin and Stiefelhagen, Rainer},
journal={IEEE Transactions on Image Processing},
volume={30},
pages={1866--1881},
year={2021},
publisher={IEEE}
}
```