README.md

---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
license: apache-2.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
pretty_name: DeLiVER
tags:
- multimodal
- autonomous-driving
- lidar
- event-camera
- depth
- rgb
- semantic-segmentation
- cvpr-2023
---

# DeLiVER: Delivering Arbitrary-Modal Semantic Segmentation

[CVPR 2023] Official Dataset Repository for the **DeLiVER** benchmark.

- **Project Page:** https://jamycheung.github.io/DELIVER.html
- **GitHub Repository:** https://github.com/InSAI-Lab/DELIVER
- **Paper:** [arXiv:2303.01480](https://arxiv.org/abs/2303.01480)
- **Model Checkpoints:** [InSAI-Lab/CMNeXt](https://huggingface.co/InSAI-Lab/CMNeXt)

---

## Dataset Description

To conduct arbitrary-modal semantic segmentation, we created the **DeLiVER** benchmark, covering **De**pth, **Li**DAR, multiple **V**iews, **E**vents, and **R**GB.
It includes 4 adverse weather conditions (**cloudy, foggy, night-time, sunny**) and 5 sensor failure corner cases:
- **MB:** Motion Blur
- **OE:** Over-Exposure
- **UE:** Under-Exposure
- **LJ:** LiDAR-Jitter
- **EL:** Event Low-resolution

Each sample has 6 views, 4 modalities, and 2 annotation types (semantic and instance).

## File Structure

The dataset archive `DELIVER.tar.gz` (~12.2 GB) unpacks into:

```text
DELIVER/
├── depth/
│   ├── cloud/ (test, train, val)
│   ├── fog/
│   ├── night/
│   ├── rain/
│   └── sun/
├── event/
├── hha/
├── img/
├── lidar/
└── semantic/
```

## Quick Start & Download

Using the Hugging Face CLI:

```bash
# Download dataset archive
hf download InSAI-Lab/DELIVER DELIVER.tar.gz --type dataset --local-dir ./data

# Extract archive
cd ./data
tar -zxvf DELIVER.tar.gz
```

Using Python (`huggingface_hub`):

```python
from huggingface_hub import hf_hub_download

dataset_path = hf_hub_download(
    repo_id="InSAI-Lab/DELIVER",
    repo_type="dataset",
    filename="DELIVER.tar.gz",
    local_dir="./data"
)
```

## Citation

```bibtex
@inproceedings{zhang2023delivering,
  title={Delivering Arbitrary-Modal Semantic Segmentation},
  author={Zhang, Jiaming and Liu, Ruiping and Shi, Hao and Yang, Kailun and Rei{\ss}, Simon and Peng, Kunyu and Fu, Haodong and Wang, Kaiwei and Stiefelhagen, Rainer},
  booktitle={CVPR},
  year={2023}
}

@article{zhang2023cmx,
  title={CMX: Cross-modal fusion for RGB-X semantic segmentation with transformers},
  author={Zhang, Jiaming and Liu, Huayao and Yang, Kailun and Hu, Xinxin and Liu, Ruiping and Stiefelhagen, Rainer},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2023}
}
```

## License

This dataset is released under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).