Datasets:

Yuliang
/

DART

	---
	license: mit
	task_categories:
	- image-to-3d
	tags:
	- hand model
	- 3d reconstruction
	- mano
	- synthetic
	- textures
	- accessories
	size_categories:
	- 100K<n<1M
	language:
	- en
	pretty_name: DART
	---

	<p align="center">

	<h1 align="center">DART: Articulated Hand Model with Diverse Accessories and Rich Textures</h1>
	<p align="center">
	<a href="https://tomguluson92.github.io/"><strong>Daiheng Gao</strong><sup>*</sup></a>
	·
	<a href="https://ps.is.tuebingen.mpg.de/person/yxiu"><strong>Yuliang Xiu</strong><sup>*</sup></a>
	·
	<a href="https://kailinli.top/#"><strong>Kailin Li</strong><sup>*</sup></a>
	·
	<a href="https://lixiny.github.io/"><strong>Lixin Yang</strong><sup>*</sup></a>
	<br>
	<strong>Feng Wang</strong>
	·
	<strong>Peng Zhang</strong>
	·
	<strong>Bang Zhang</strong>
	·
	<a href="https://www.mvig.org/"><strong>Cewu Lu</strong></a>
	·
	<a href="https://www.cs.sfu.ca/~pingtan/"><strong>Ping Tan</strong></a>
	</p>
	<h2 align="center">NeurIPS 2022 (Datasets and Benchmarks Track)</h2>
	<table align="center" style="width: 60%;">
	<tr>
	<td><a href='https://arxiv.org/abs/2210.07650'>
	<img src='https://img.shields.io/badge/Paper-PDF-green?style=for-the-badge&logo=arXiv&logoColor=green' alt='Paper PDF'>
	</a></td>
	<td><a href='https://dart2022.github.io/'>
	<img src='https://img.shields.io/badge/DART-Page-orange?style=for-the-badge&logo=Google%20chrome&logoColor=orange' alt='Project Page'>
	</a></td>
	<td><a href='https://github.com/DART2022/DART'>
	<img src='https://img.shields.io/badge/DART-Code-blue?style=for-the-badge&logo=Github&logoColor=blue' alt='Github code'>
	</a></td>
	<td><a href="https://www.youtube.com/watch?v=kvWqtdLf6hs">
	<img alt="youtube views" src="https://img.shields.io/youtube/views/ZufrPvooR2Q?logo=youtube&labelColor=ce4630&style=for-the-badge"/></a></td>
	</tr>
	</table>
	<div align="center">
	<img src="https://dart2022.github.io/img/teaser.png" alt="Logo" width="100%">
	</div>
	</p>

	<br />
	<br />

	## Update

	- [2022.10.07] DART's raw textures+accessories are released at [RAW](https://drive.google.com/file/d/1_KPzMFjXLHagPhhos7NXvzdzMMN-b1bd/view)
	- [2022.09.29] DART Unity GUI's source code is publicly available at [GUI](https://drive.google.com/file/d/1xtfc-fMHR5ax-e5S5Drx53Rm2ddL5mHs/view?usp=sharing).

	## Environment

	- numpy
	- cv2
	- imageio
	- PyTorch
	- PyTorch3D (>= 0.6)
	- [manotorch](https://github.com/lixiny/manotorch.git)

	## Data

	Please download the data from [HuggingFace/Dataset](https://huggingface.co/datasets/yuliang/dart) or [Baidu Pan (4w3r)](https://pan.baidu.com/share/init?surl=xOV3FkNFxNS-mYrHTXd8Iw) and put them in the `data/DARTset` folder.

	```bash
	git clone https://huggingface.co/datasets/yuliang/dart data/DARTset
	```

	Then download [MANO](https://mano.is.tue.mpg.de) from the official website and put it in the `assets` folder.

	Your directory should look like this:

	```
	.
	├── DARTset.py
	├── DARTset_utils.py
	├── assets
	│ └── mano_v1_2
	├── data
	│ └── DARTset
	│ ├── train
	│ │ ├── 0
	│ │ ├── 0_wbg
	│ │ ├── part_0.pkl
	│ │ \|-- ...
	│ └── test
	```

	## Visualization

	```python
	python DARTset.py
	```

	You can modify this [line](https://github.com/DART2022/DARTset/blob/f619f609b1902b344fc5bbba57d080763a5496eb/DARTset.py#L175) in DARTset.py to change the `train/test` data split.

	## Post Processing with Unity GUI

	Please check [postprocess folder](https://github.com/DART2022/DART/blob/master/postprocess/README.md) to learn how to generate intermediate output using DART's Unity GUI.

	## Citation

	If you find our work useful in your research, please cite:

	```
	@inproceedings{gao2022dart,
	title={{DART: Articulated Hand Model with Diverse Accessories and Rich Textures}},
	author={Daiheng Gao and Yuliang Xiu and Kailin Li and Lixin Yang and Feng Wang and Peng Zhang and Bang Zhang and Cewu Lu and Ping Tan},
	booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
	year={2022},
	}

	```