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WildCity
Yuto Furutani*, Takashi Otonari*, Kaede Shiohara*,
Toshihiko Yamasaki
The University of Tokyo. *Co-first authors.
Overview
Our WildCity dataset is designed to train feed-forward 3DGS models for 3D reconstruction from unconstrained photo collections. The dataset comprises multi-view, multi-lighting images covering 200 scenes, 170 HDRI maps, and diverse transient objects.
Dataset Structure
license.csv # Attribution info for all 3D models used
scene_city_mapping.csv # Mapping from scene names to city IDs
wildcity/ # Main dataset: 200 scenes
βββ 0_visualization/ # Overview PDFs for all scenes
βββ Scene{1..200}/
βββ Cam_{000..049}/ # 50 camera viewpoints per scene
β βββ light_{000..029}.png # 30 illumination conditions
β βββ depth.exr # Depth map
β βββ mask.png # Sky mask
βββ colmap/
βββ cameras.txt # Camera intrinsics
βββ images.txt # Camera extrinsics
wildcity_aug/ # Augmented subset
βββ Scene{...}/
βββ Cam_{000..049}/
βββ light_{000..029}.png # Randomly sampled viewpoints
Image Resolutions
wildcity: 512x512 pixelswildcity_aug: 1024x1024 pixels
wildcity contains the original multi-illumination renders.wildcity_aug is a randomly sampled subset (1/8 of wildcity scenes) with transient objects inserted via Gemini. Where the same scene, camera, and illumination exist in both splits (e.g., wildcity/Scene1/Cam_000/light_003.png and wildcity_aug/Scene1/Cam_000/light_003.png), the images differ only in the presence of transient objects.
License
Licenses vary by city, as the underlying 3D assets carry different terms. Per-model details are in license.csv; scene-to-city mappings are in scene_city_mapping.csv.
| City | Scenes | License |
|---|---|---|
| city1 | Scene1β25 | CC BY |
| city2 | Scene26β50 | CC BY-NC |
| city3 | Scene51β72 | CC BY-NC |
| city4 | Scene73β96 | CC BY |
| city5 | Scene97β117 | CC BY-NC |
| city6 | Scene118β135 | CC BY-SA |
| city7 | Scene136β150 | CC BY-SA |
| city8 | Scene151β175 | CC BY |
| city9 | Scene176β200 | CC BY |
Citing
@article{furutani2026wild3r,
title = {Wild3R: Feed-Forward 3D Gaussian Splatting from Unconstrained Sparse Photo Collection},
author = {Furutani, Yuto and Otonari, Takashi and Shiohara, Kaede and Yamasaki, Toshihiko},
journal = {arXiv preprint arXiv:2606.11894},
year = {2026}
}
Acknowledgements
We thank all authors behind these projects and repositories for their excellent work: LightCity, SceneCity, Sketchfab, and Gemini.
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