360Loc: Omnidirectional Visual Localization with Cross-device Queries

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360Loc: A Dataset and Benchmark for Omnidirectional Visual Localization with Cross-device Queries
Huajian Huang*¹, Changkun Liu*¹, Yipeng Zhu¹, Hui Cheng², Tristan Braud¹ and Sai-Kit Yeung¹
* equal contribution
The Hong Kong University of Science and Technology¹, Sun Yat-Sen University²
In Proceedings of Computer Vision and Pattern Recognition Conference (CVPR), 2024

Usage

To save the store space and facilitate data access, we only store the original 360-degree images of query and inference. You can use this tool to generate required images in fisheye and pinhole cameras.

git clone https://github.com/HuajianUP/360Loc.git
pip install json tqdm yaml numpy opencv-python requests

You can download the 360Loc dataset link and unzip them in the folder ./360Loc.

360Loc
├── atrium
│   ├── camera_config
│   ├── pose
│   ├── mapping
│   ├── query_360
│   ├── query_pinhole
│   ├── query_fisheye1
│   ├── query_fisheye2
│   └── query_fisheye3
├── ....
│
└── piatrium
    ├── camera_config
    ├── ....
    └── query_fisheye3

And then run the below command to process the data.

python process.py --dir PATH_TO_360LOC_DATASET

We also provide a script to download and process the 360Loc dataset automatically.

python onekey.py --dir PATH_TO_SAVE_360LOC_DATASET

Pose Format

We provide both json poses files and txt poses files.

For .json poses files: We give 4*4 matrix image_name: [R|T]， T are camera to world coordinates.

For .txt poses files: image_name x y z qw qx qy qz.

x, y, z are camera to world coordinates. Our 6DoF poses follow the COLMAP coordinate system.

Citation

@inproceedings{360Loc,
    title = {360Loc: A Dataset and Benchmark for Omnidirectional Visual Localization with Cross-device Queries},
    author = {Huang, Huajian and Liu, Changkun and Zhu, Yipeng and Cheng Hui and Braud, Tristan and Yeung, Sai-Kit},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year = {2024}
}