| --- |
| language: |
| - en |
| - ja |
| license: cc-by-nc-4.0 |
| pretty_name: 360CityArena |
| arxiv: 2608.08814 |
| size_categories: |
| - n<1K |
| tags: |
| - benchmark |
| - embodied-ai |
| - multimodal |
| - visual-reasoning |
| - navigation |
| - 360-degree |
| - unity |
| - image |
| - tabular |
| - datasets |
| --- |
| |
| # 360CityArena |
|
|
| 360CityArena is a Unity-based embodied navigation and visual reasoning benchmark |
| for multimodal large language models. This dataset release contains 175 tasks |
| across seven task families and the reference images required by those tasks. |
|
|
| *August 11, 2026: Task 7006 was corrected after we found that it duplicated task 7009.* |
|
|
| - [Paper page](https://huggingface.co/papers/2608.08814) |
| - [Project page](https://360mm-team.github.io/360CityArena/) |
| - [GitHub repository](https://github.com/360MM-Team/360CityArena) |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("hal-utokyo/360CityArena") |
| test = dataset["test"] |
| print(test.num_rows) # 175 |
| print(test[0]) |
| ``` |
|
|
| The `reference_image` field is an image for tasks that require one and `None` |
| otherwise. There are 75 task rows with a reference image and 51 unique image |
| files: one localization map shared by 25 tasks, 25 landmark images, and 25 |
| navigation maps. |
|
|
| ## Task inventory |
|
|
| | Task family | Tasks | |
| | --- | ---: | |
| | Localization | 25 | |
| | Landmark Search with Language | 25 | |
| | Landmark Search with Image | 25 | |
| | Counting | 25 | |
| | Map Navigation | 25 | |
| | Language Guided Navigation | 25 | |
| | Relational Spatial Reasoning | 25 | |
|
|
| All records are in the `test` split because 360CityArena is an evaluation |
| benchmark, not a training corpus. |
|
|
| ## Record fields |
|
|
| Each row contains the task ID and family, difficulty, initial environment index, |
| task prompt, ground-truth answer, and task-specific goal fields. |
| `reference_image_path` identifies the corresponding runner asset while |
| `reference_image` provides the image directly through 🤗 Datasets and the Dataset |
| Viewer. The legacy `source_file`, `source_row`, and `source_record` fields retain |
| provenance from the initial Hub migration. |
|
|
| ## Intended use and limitations |
|
|
| The dataset is intended for evaluating embodied multimodal agents with the |
| 360CityArena Unity environment and runner. Loading this dataset alone does not |
| run the interactive benchmark; use the code and evaluation protocol in the |
| GitHub repository. The benchmark covers a fixed virtual reconstruction of an |
| urban area and should not be treated as evidence of general navigation ability, |
| physical-world safety, or geographic coverage. Some reference images contain |
| Japanese storefront text and other scene-specific visual information. |
|
|
| ## License and attribution |
|
|
| Dataset records and benchmark assets are distributed under the Creative Commons |
| Attribution-NonCommercial 4.0 International license (CC BY-NC 4.0), except where |
| third-party terms apply. Map-derived assets include OpenStreetMap data: |
| copyright OpenStreetMap contributors, available under the Open Database License |
| (ODbL). See the repository's `DATA_LICENSE` and `NOTICE` files for details. |
|
|
| The benchmark runner and other source code are separately licensed under |
| Apache-2.0 in the GitHub repository. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{watanabe2026360cityarena, |
| title = {360CityArena: A Realistic Virtual Urban Navigation Benchmark for Embodied Agents}, |
| author = {Watanabe, Kenta and Miyai, Atsuyuki and Takenawa, Mizuki and Aizawa, Kiyoharu and Yamasaki, Toshihiko}, |
| booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)}, |
| year = {2026} |
| } |
| ``` |
|
|
