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DART: Articulated Hand Model with Diverse Accessories and Rich Textures (NeurIPS 2022 - Datasets and Benchmarks Track)

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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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Update

  • [2024.04.01]DARTset could be easily cloned from Huggingface/Dataset atDARTset
  • [2022.10.07]DART's raw textures+accessories are released atRAW
  • [2022.09.29]DART Unity GUI's source code is publicly available atGUI

Environment

  • numpy
  • cv2
  • imageio
  • PyTorch
  • PyTorch3D (>= 0.6)
  • manotorch

Data

Please download the data fromHuggingFace orBaidu Pan (4w3r) and put them in thedata/DARTset folder.

git clone https://huggingface.co/datasets/Yuliang/DART data/DARTset

Then downloadMANO from the official website and put it in theassets 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

pythonDARTset.py

You can modify thisline in DARTset.py to change thetrain/test data split.

Post Processing with Unity GUI

Please checkpostprocess 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},}

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DART: Articulated Hand Model with Diverse Accessories and Rich Textures (NeurIPS 2022 - Datasets and Benchmarks Track)

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