README.md

<h1 align="center">[ECCV 2026] Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond</h1>

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  <a href="https://jou719.github.io/Holo360D_homepage/"><img src="https://img.shields.io/badge/Project%20Page-5745BB?logo=google-chrome&logoColor=white"></a> &ensp;
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<div align="center">
  <img src="assets/teaser.jpg" width="1100px" alt="Teaser Image">
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## 🎉 NEWS
- [2026.07.04] 🔥 We have fixed incorrect RGB face masks within the Holo360D **test set**. If you downloaded **the test set before July 2, 2026**, please re-download the updated test dataset.
- [2026.07.01] 🔥 We have released the inference code for **fine-tuned Pi3** on the Holo360D, which supports both **single-view and multi-view panoramic 3D reconstruction**.
- [2026.06.27] 🔥 We have released all data of the **Holo360D** dataset on Hugging Face, featuring 56 indoor scenes and 19 outdoor scene.
- [2026.06.18] 🎉 **Holo360D** has been accepted by ECCV 2026.
- [2026.06.03] 🔥 We have released test data of the **Holo360D** dataset on Hugging Face, featuring 13 indoor scenes and 4 outdoor scene.

---

## ✨ Overview

We present Holo360D, the first large-scale real-world panoramic 3D dataset, containing 109,495 panoramas paired with LiDAR-derived ground truth, including precise meshes, point clouds, depth maps, and camera poses. More importantly, Holo360D is the first panoramic dataset to offer accurately aligned high-completeness depth
maps with continuous camera trajectories over long sequences.

Key characteristics (from the paper):
- Large-scale real-world 360 panorama 3D dataset.
- Continuous trajectory capture for multi-view settings.
- Accurately aligned high-completeness depth maps for training and testing.
- A benchmark setup for model fine-tuning and evaluation.

## 🔮 Inference
We have released the inference code and checkpoint for fine-tuned Pi3 on the Holo360D ([click here](https://github.com/Jou719/Holo360D/tree/main/Pi3_Finetuned_Holo360d))

## 📦 Dataset Structure
```
Holo360D/
├── train/
│   ├── Indoor_xxx/
│   │   ├── rgb/                # panoramic RGB images (.jpg)
│   │   ├── depth/              # depth maps (.exr)
│   │   │   ├── mesh_depth/             # depth maps (.exr)
│   │   │   ├── pointcloud_depth/       # depth maps (.exr)
│   │   │   ├── visual_mesh_depth/      # visualization (.jpg)
│   │   │   └── visual_pointcloud_depth/# visualization (.jpg)
│   │   ├── mask/               # masks (.jpg)
│   │   └── poses/              # camera poses (.txt)
│   ├── Indoor_xxx/
│   ├── Outdoor_xxx/
│   │   ├── rgb/                # panoramic RGB images (.jpg)
│   │   ├── depth/
│   │   │   ├── mesh_depth/             # depth maps (.exr)
│   │   │   ├── pointcloud_depth/       # depth maps (.exr)
│   │   │   ├── visual_mesh_depth/      # visualization (.jpg)
│   │   │   └── visual_pointcloud_depth/# visualization (.jpg)
│   │   ├── mask/               # masks (.jpg)
│   │   └── poses/              # camera poses (.txt)
│   ├── Outdoor_xxx/
│   └── ...
└── test/
    ├── Indoor_xxx/
    │   ├── rgb/
    │   ├── depth/
    │   │   ├── mesh_depth/             # depth maps (.exr)
    │   │   ├── pointcloud_depth/       # depth maps (.exr)
    │   │   ├── visual_mesh_depth/      # visualization (.jpg)
    │   │   └── visual_pointcloud_depth/# visualization (.jpg)
    │   ├── mask/
    │   └── poses/
    ├── Indoor_xxx/
    ├── Outdoor_xxx/
    │   ├── rgb/
    │   ├── depth/
    │   │   ├── mesh_depth/
    │   │   ├── pointcloud_depth/
    │   │   ├── visual_mesh_depth/
    │   │   └── visual_pointcloud_depth/
    │   ├── mask/
    │   └── poses/
    ├── Outdoor_xxx/
    └── ...
```

Notes:
- Timestamp-like file names are shared across modalities to support frame-level alignment.

## 💡 Dataset Download

Detailed download links and full-package release plan are **to be released**.

- [Hugging Face](https://huggingface.co/datasets/ouou123/Holo360D/tree/main)

## 📬 Contact

If you have any other questions, you can open an issue on GitHub or contact us via email at jou719@connect.hkust-gz.edu.cn.

## Citation
If you find this dataset useful, please cite our paper.

```bibtex
@article{ou2026holo360d,
  title={Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond},
  author={Ou, Jing and Cao, Zidong and Ren, Yinrui and Li, Zhuoxiao and Zhu, Jinjing and Hua, Tongyan and Zhang, Shuai and Xiong, Hui and Zhao, Wufan},
  journal={arXiv preprint arXiv:2604.22482},
  year={2026}
}
```