Datasets:
metadata
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
DART: Articulated Hand Model with Diverse Accessories and Rich Textures
Daiheng Gao*
·
Yuliang Xiu*
·
Kailin Li*
·
Lixin Yang*
Feng Wang
·
Peng Zhang
·
Bang Zhang
·
Cewu Lu
·
Ping Tan
NeurIPS 2022 (Datasets and Benchmarks Track)
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![Logo](https://dart2022.github.io/img/teaser.png)
Update
- [2022.10.07] DART's raw textures+accessories are released at RAW
- [2022.09.29] DART Unity GUI's source code is publicly available at GUI.
Environment
- numpy
- cv2
- imageio
- PyTorch
- PyTorch3D (>= 0.6)
- manotorch
Data
Please download the data from HuggingFace/Dataset or Baidu Pan (4w3r) and put them in the data/DARTset
folder.
git clone https://huggingface.co/datasets/yuliang/dart data/DARTset
Then download MANO 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 DARTset.py
You can modify this line in DARTset.py to change the train/test
data split.
Post Processing with Unity GUI
Please check postprocess folder 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},
}