Blame for README.md

---
pretty_name: OccStress
viewer: false
license: other
license_name: occstress-source-dependent-terms
license_link: https://huggingface.co/datasets/insailab/OccStress/blob/main/DISTRIBUTION.md
task_categories:
  - other
tags:
  - 3d
  - timeseries
  - occupancy-forecasting
  - robustness
  - autonomous-driving
  - nuscenes
  - waymo
  - carla
---


<p align="center">
  <img src="assets/occstress-logo.png" width="88" alt="OccStress logo">
</p>

<h1 align="center">OccStress</h1>

<p align="center">
  <strong>Stress-Testing the 4D Occupancy Forecasting Chain</strong><br>
  NeurIPS 2026 &middot; Evaluations and Datasets Track
</p>

<p align="center">
  <a href="https://insailab.org/OccStress/"><img src="https://img.shields.io/badge/Project_Page-444444?style=flat-square&amp;logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9IndoaXRlIiBzdHJva2Utd2lkdGg9IjIiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIgc3Ryb2tlLWxpbmVqb2luPSJyb3VuZCIgY2xhc3M9Imx1Y2lkZSBsdWNpZGUtZ2xvYmUiIGFyaWEtaGlkZGVuPSJ0cnVlIj48Y2lyY2xlIGN4PSIxMiIgY3k9IjEyIiByPSIxMCI%2BPC9jaXJjbGU%2BPHBhdGggZD0iTTEyIDJhMTQuNSAxNC41IDAgMCAwIDAgMjAgMTQuNSAxNC41IDAgMCAwIDAtMjAiPjwvcGF0aD48cGF0aCBkPSJNMiAxMmgyMCI%2BPC9wYXRoPjwvc3ZnPg%3D%3D" alt="Project Page"></a>
  <a href="https://arxiv.org/abs/2512.15621"><img src="https://img.shields.io/badge/Paper-444444?style=flat-square&amp;logo=arxiv&amp;logoColor=white" alt="Paper on arXiv"></a>
  <a href="https://github.com/FaterYU/OccStress"><img src="https://img.shields.io/badge/Code-444444?style=flat-square&amp;logo=github&amp;logoColor=white" alt="Code on GitHub"></a>
  <a href="https://insailab.org/OccStress/leaderboard/"><img src="https://img.shields.io/badge/Leaderboard-444444?style=flat-square&amp;logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9IndoaXRlIiBzdHJva2Utd2lkdGg9IjIiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIgc3Ryb2tlLWxpbmVqb2luPSJyb3VuZCIgY2xhc3M9Imx1Y2lkZSBsdWNpZGUtY2hhcnQtbm8tYXhlcy1jb2x1bW4taW5jcmVhc2luZyIgYXJpYS1oaWRkZW49InRydWUiPjxwYXRoIGQ9Ik01IDIxdi02Ij48L3BhdGg%2BPHBhdGggZD0iTTEyIDIxVjkiPjwvcGF0aD48cGF0aCBkPSJNMTkgMjFWMyI%2BPC9wYXRoPjwvc3ZnPg%3D%3D" alt="Leaderboard"></a>
</p>

<p align="center">
  <a href="#download">Download</a> &nbsp;&middot;&nbsp;
  <a href="#dataset-coverage">Coverage</a> &nbsp;&middot;&nbsp;
  <a href="FORMAT.md">Data Format</a> &nbsp;&middot;&nbsp;
  <a href="DISTRIBUTION.md">Licenses and Use</a>
</p>

**How do perception errors affect future occupancy forecasts?** OccStress
evaluates robustness across the occupancy forecasting chain, from sensor errors
to 3D occupancy states and multi-horizon predictions.

![OccStress overview: upstream and manual tracks, temporal protocols, and occupancy forecasting.](assets/overview.png)

<p align="center">
  <strong>3 datasets &middot; 10,827 unique anchors &middot; 975 protocols &middot; 6 future horizons</strong>
</p>

This repository provides **evaluation protocols, derived occupancy assets and
supporting metadata**. All **75 archives are available**, totaling **40.95 GB
compressed** and **143.67 GB extracted** including metadata. Download only the
dataset, track or upstream source you need.

Original camera images, LiDAR, clean GT and model checkpoints are **not bundled**.
See [external prerequisites](EXTERNAL_DATA.md) and [source-dependent terms](DISTRIBUTION.md).

## Dataset Coverage

| Dataset | Source | Scenes | Anchors per protocol |
| --- | --- | ---: | ---: |
| **OccStress-nuScenes** | nuScenes / Occ3D | 150 | 4,519 |
| **OccStress-Waymo** | Waymo / Occ3D | 202 | 5,978 |
| **OccStress-CARLA** | UniOcc CARLA simulation | 3 | 330 |

All datasets use **2 Hz observations**, a canonical window of four historical
states plus the current state, and six future targets at **+0.5 to +3.0 seconds**.
The selected frames total 6,019 / 7,998 / 360 for nuScenes / Waymo / CARLA.

| Published protocols | nuScenes | Waymo | CARLA |
| --- | ---: | ---: | ---: |
| Manual | 38 | 38 | 38 |
| Upstream | 364 | 219 | 218 |
| Position sweep | 60 | 0 | 0 |

Counts include clean references. **Protocols reuse anchors and assets**;
975 protocols do not represent 975 independent datasets or new sets of samples.
Waymo's two EFFOcc sensor-stress branches retain separate clean protocol files.

## What Can You Evaluate?

- **Upstream robustness:** use source-specific occupancy predictions under
  camera or LiDAR stressors to measure error propagation into forecasting.
- **Manual robustness:** test semantic replacement, dropout, holes,
  misalignment and traffic mirroring directly in occupancy states.
- **Temporal sensitivity:** compare Current-only, Recent-burst and History-only
  failure regimes, or use the fixed-budget, single-state position sweep to
  isolate input-position effects.

Traffic mirroring transforms inputs, targets and motion metadata consistently
and is reported separately from non-traffic robustness. Four-state models do
not observe the earliest canonical input; that position is marked unobserved,
not robust. See [format and evaluation conventions](FORMAT.md).

## Download

### Start With One Dataset and Track

For example, download the **Waymo manual track** and its metadata:

```bash
python -m pip install -U huggingface_hub
hf download insailab/OccStress --repo-type dataset \
  --local-dir /datasets/OccStress-download \
  --include README.md DOWNLOAD.md FORMAT.md EXTERNAL_DATA.md DISTRIBUTION.md packages.json \
  'metadata/common.tar.zst' 'metadata/OccStress-Waymo.tar.zst' \
  'archives/manual/OccStress-Waymo/*.tar.zst'
```

Use [DOWNLOAD.md](DOWNLOAD.md) for other tracks, source-specific selection,
pinned revisions, checksum verification and extraction commands.
The [package index](packages.json) lists every archive's size and SHA256.

Extract selected archives into one shared `OccStress/` root, then prepare
[external GT and metadata](EXTERNAL_DATA.md) before running a model.
Reserve space for both downloaded archives and their extracted contents;
original dependencies need additional storage.

<details>
<summary><strong>What is inside the extracted dataset?</strong></summary>

```text
OccStress/
  meta/<dataset>/                   Dataset metadata and controls
  protocols/manual/<dataset>/      Manual evaluation protocols
  protocols/upstream/<dataset>/    Source-specific evaluation protocols
  protocols/position_sweep/        Single-state temporal diagnostics
  occ/manual/<dataset>/            Shared manual corruption assets
  occ/upstream/<dataset>/          Exported upstream occupancy
  events/manual/<dataset>/         Corruption event metadata
```

`<dataset>` is `OccStress-nuScenes`, `OccStress-Waymo` or `OccStress-CARLA`.
Protocol paths are relative to this root. Position sweeps reuse the existing
occupancy assets; they do not need duplicate voxel packs. See [FORMAT.md](FORMAT.md).

</details>

## Before Evaluation

- **Use the matching ground truth.** Native Waymo labels require the supplied
  mapping; CARLA requires the canonical right-handed view. Already converted
  occupancy arrays must not be transformed twice.
- **Keep the model's input and control policy.** Use all six genuine future
  targets; do not substitute a current-frame reconstruction.
- **Keep metric conventions explicit.** Historical paper metrics and the
  released present-class convention are not interchangeable. Paper averages
  use the 1, 2 and 3 second horizons.
- **Use the assets directly when applicable.** Occupancy-input forecasting
  does not require upstream weights or original sensors. Camera-direct methods
  and upstream re-export do require the relevant sensor inputs.

This is an **archive-based benchmark**, not an Arrow table for
`datasets.load_dataset`. Only unpickle protocol files from trusted sources.

## Scope and Limitations

OccStress is a controlled diagnostic stress test, **not a deployment-risk
estimate or safety certification**. Its corruptions are reproducible stress
conditions, not a calibrated distribution of real-world failures.

CARLA contains only three simulated validation scenes. The datasets differ in
class support and sensor configuration; report cross-dataset and zero-shot
settings explicitly. Published protocols do not imply that every model supports
every track or that every model/protocol combination has been evaluated.

Preparation checks and their scope are recorded in [FORMAT.md](FORMAT.md#validation-scope)
and the published manifests. Source-dataset registration, attribution and use
conditions still apply; see [DISTRIBUTION.md](DISTRIBUTION.md).

## Croissant Metadata

De-anonymized [Croissant 1.1 metadata](croissant/README.md) is available for
all three datasets, including Responsible AI documentation and provenance.

[Camera-ready ZIP](croissant/OccStress-Croissant.zip) ·
[nuScenes JSON](croissant/OccStress-nuScenes.json) ·
[Waymo JSON](croissant/OccStress-Waymo.json) ·
[CARLA JSON](croissant/OccStress-CARLA.json)

The metadata links the original packages and provides machine-readable anchor,
protocol and label-map indexes. It does not replace the voxel loaders or the
[external ground-truth prerequisites](EXTERNAL_DATA.md).

## Citation

```bibtex
@inproceedings{zheng2026occstress,
  title = {{OccStress}: Stress-Testing the {4D} Occupancy Forecasting Chain},
  author = {Zheng, Yu and Hu, Jie and Xiong, Jiaqi and Liu, Ruiping and Zheng, Junwei and Yang, Kailun and Zhang, Jiaming},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2026},
  url = {https://arxiv.org/abs/2512.15621}
}
```

Please also cite the source datasets, corruption operators and upstream models
used in your evaluation. Source references are listed in [FORMAT.md](FORMAT.md#sources).

For dataset issues, open a [discussion](https://huggingface.co/datasets/insailab/OccStress/discussions)
with the dataset, protocol path, revision and error message. Do not post tokens
or private source-data links.