| --- |
| license: cc-by-nc-sa-4.0 |
| pretty_name: RoboGeo |
| task_categories: |
| - object-detection |
| tags: |
| - autonomous-driving |
| - bev-perception |
| - robustness |
| - multi-camera |
| - carla |
| - synthetic |
| size_categories: |
| - 100B<n<1T |
| configs: |
| - config_name: default |
| data_files: |
| - split: platform_layouts |
| path: platform_layouts/*.tar |
| - split: viewpoint_perturbation |
| path: viewpoint_perturbation/*.tar |
| --- |
| |
| # RoboGeo: Benchmarking Camera-Geometry Robustness in Multi-Camera BEV Perception |
|
|
| **WACV 2027 · Evaluations & Datasets Track.** A CARLA-based benchmark that measures how robust |
| multi-camera BEV perception models (3D detection and BEV segmentation) are to |
| **camera-geometry changes**: viewpoint perturbation (**VP**) and cross-sensor |
| transfer (**CTS**) across three ego-vehicle platforms (**sedan / suv / bus**). |
|
|
| ## What's inside |
|
|
| | component | files | size | contents | |
| |---|---|---|---| |
| | `metadata/carla_geobev_meta.tar.zst` | 1 | 1.5 GB | nuScenes-format DBs `v1.0-carla_{sedan,suv,bus}` (train, 220 scenes) + `..._eval` (eval, 49 scenes), `split/{train,val}.txt`, detection info `.pkl`s | |
| | `platform_layouts/RGB-*.tar` | 18 | 256 GB | multi-camera RGB sweeps: 3 vehicles × 6 cameras (`RGB-CAM_*` = sedan, `RGB-suv-CAM_*`, `RGB-bus-CAM_*`) | |
| | `viewpoint_perturbation/RGB-*.tar` (+`viewpoint_metadata.json`) | 186 | ~545 GB | VP evaluation captures: 6 cameras × 31 camera-pose variants (yaw/pitch/roll sweeps), 50 scenes; per-variant extrinsics in `viewpoint_metadata.json` | |
|
|
| ## Setup |
|
|
| ```bash |
| mkdir -p carla_geobev carla_VR |
| |
| # metadata + images → carla_geobev/ |
| tar -I zstd -xf metadata/carla_geobev_meta.tar.zst -C carla_geobev |
| for t in platform_layouts/*.tar; do tar -xf "$t" -C carla_geobev; done # creates carla_geobev/sweeps/RGB-*/ |
| |
| # viewpoint-perturbation captures → carla_VR/ |
| cp viewpoint_perturbation/viewpoint_metadata.json carla_VR/ |
| for t in viewpoint_perturbation/*.tar; do tar -xf "$t" -C carla_VR; done # creates carla_VR/sweeps/RGB-*_yaw*pitch*roll*/ |
| ``` |
|
|
| The extracted `carla_geobev/` is what the benchmark configs point to as the data |
| root (nuScenes-style layout). All paths inside the DBs and `.pkl`s are relative: |
| the DB JSONs and `carla_infos_*.pkl` use `sweeps/RGB-*/...` (relative to |
| `carla_geobev/`), while `{sedan,suv,bus}_infos_*.pkl` follow the mmdet3d |
| convention `data/nuscenes/sweeps/...` — symlink your extracted `carla_geobev/` |
| to `<repo>/data/nuscenes` for those. The pkls also reference |
| `sweeps/LIDAR/*.npz` entries; LiDAR files are not part of this release |
| (camera-only evaluation never loads them — see "Not included"). |
|
|
| ### Frame-rate note (important) |
|
|
| `carla_geobev` is a temporally subsampled (1/2-rate) annotation of the capture: |
| **`carla_geobev` frame `N` corresponds to `carla_VR` frame `2N`.** The `viewpoint_perturbation` |
| shards here contain only the even VR frames — exactly the frames that have |
| ground truth — so filenames in `carla_VR` carry frame numbers `2N`. |
|
|
| ### Not included |
|
|
| - DPT depth maps and instance-segmentation renders (derived data; regenerable |
| from RGB — see the benchmark code repo). |
| - BEV segmentation occupancy labels and raw LiDAR (available on request; |
| `num_lidar_pts` / visibility attributes are already baked into the info pkls). |
|
|
| ## Benchmark |
|
|
| Evaluation covers 3D detection (BEVFormer, BEVDet, BEVDepth, DETR3D, PETR/CAPE, |
| DFA3D, PD-BEV) and BEV segmentation (CVT, GaussianLSS, LaRa, LSS, PointBEV, |
| SimpleBEV) under Normal / VP (Ext-swap, Img-swap, Cal-swap × roll/pitch/yaw) / |
| CTS (sedan→suv, sedan→bus) conditions. Code and evaluation harness: |
| **available soon**. |
|
|
| ## License & attribution |
|
|
| Released under **CC BY-NC-SA 4.0** (non-commercial, share-alike, attribution). |
|
|
| This dataset was generated by **replaying [SimBEV](https://github.com/goodarzmehr/simbev) |
| (ITSC 2026) driving logs in [CARLA](https://carla.org)** and re-rendering all sensors. It |
| contains no original SimBEV files; it is a SimBEV derivative released with the |
| SimBEV authors' permission under the same CC BY-NC-SA 4.0 terms. If you use |
| RoboGeo, please also acknowledge and cite SimBEV and CARLA: |
|
|
| ```bibtex |
| @article{mehr2025simbev, |
| title = {SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset}, |
| author = {Mehr, Goodarz and Eskandarian, Azim}, |
| journal = {arXiv preprint arXiv:2502.01894}, |
| year = {2025} |
| } |
| |
| @inproceedings{carla, |
| title = {{CARLA}: An Open Urban Driving Simulator}, |
| author = {Dosovitskiy, Alexey and Ros, German and Codevilla, Felipe and Lopez, Antonio and Koltun, Vladlen}, |
| booktitle = {Proceedings of the 1st Annual Conference on Robot Learning (CoRL)}, |
| year = {2017} |
| } |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{robogeo2027, |
| title = {RoboGeo: Benchmarking Camera-Geometry Robustness in Multi-Camera BEV Perception}, |
| author = {Jeongtae Kim and Giyong Moon and Chanyoung Lee and Soonmin Hwang}, |
| booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, |
| year = {2027} |
| } |
| ``` |
|
|
