| --- |
| license: mit |
| pipeline_tag: robotics |
| tags: |
| - robotics |
| - grasping |
| - learning-from-humans |
| - dexterous-manipulation |
| --- |
| |
| # Human Universal Grasping (HUG) |
|
|
| HUG is a flow-matching model that generates diverse human grasps for any user-specified object in a single RGB-D image. By learning from a large-scale egocentric dataset of human grasps (1M-HUGs), the model can predict human-like grasps that can be retargeted to various robot hands for zero-shot manipulation. |
|
|
| - 📄 **Paper**: [Human Universal Grasping](https://arxiv.org/abs/2606.17054) |
| - 🌐 **Website**: [grasping.io](https://grasping.io) |
| - 💻 **Code**: [github.com/kevinywu/hug](https://github.com/kevinywu/hug) |
|
|
| ## Installation |
|
|
| The codebase is tested on Ubuntu 22.04/24.04, CUDA 12.8, PyTorch 2.9.1, and Python 3.10. |
|
|
| ```bash |
| # 1) Environment setup |
| conda env create -f environment.yaml && conda activate hug |
| pip install torch==2.9.1 torchvision==0.24.1 torchaudio==2.9.1 --index-url https://download.pytorch.org/whl/cu128 |
| pip install torch-cluster -f https://data.pyg.org/whl/torch-2.9.1+cu128.html |
| pip install --no-build-isolation git+https://github.com/mattloper/chumpy.git@580566e |
| pip install -e . |
| ``` |
|
|
| Please refer to the [official repository](https://github.com/kevinywu/hug) for instructions on downloading required assets like MANO models. |
|
|
| ## Usage |
|
|
| ### Download Weights |
|
|
| Download the full model weights (`.safetensors`) using the `huggingface-cli`: |
|
|
| ```bash |
| hf download kevinywu/hug hug_full.safetensors --local-dir checkpoints/ |
| ``` |
|
|
| ### Inference |
|
|
| HUG predicts human grasps in MANO form. You can run the interactive application to predict grasps for objects in the camera frame: |
|
|
| ```bash |
| CKPT=checkpoints/hug_full.safetensors |
| DATA=data/hug_bench/ |
| |
| # Launch the app: click an object to predict a grasp |
| python -m hug.app --checkpoint-path "$CKPT" --dataset-path "$DATA" --save-pred |
| |
| # Visualize saved predictions |
| python -m hug.visualize_predictions --dataset-path "$DATA" |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wu2026hug, |
| title={Human Universal Grasping}, |
| author={Kevin Yuanbo Wu and Tianxing Zhou and Isaac Tu and Billy Yan and Irmak Guzey and David Fouhey and Dandan Shan and Lerrel Pinto}, |
| journal={arXiv preprint arXiv:2606.17054}, |
| year={2026} |
| } |
| ``` |
