Datasets:
Tasks:
Image Segmentation
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
File size: 2,902 Bytes
9c5308d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | ---
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).
|