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Update dataset card with robotics task, paper link, and usage

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Hi! I'm Niels from the community science team at Hugging Face.

This PR improves the dataset card for the SCFields release by:
- Adding the `robotics` task category to the metadata.
- Linking the associated research paper: [Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation](https://huggingface.co/papers/2602.13833).
- Adding a sample usage section with a training command found in the official repository.
- Including the BibTeX citation.

Files changed (1) hide show
  1. README.md +41 -4
README.md CHANGED
@@ -1,15 +1,21 @@
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  ---
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  license: cc-by-nc-4.0
 
 
 
 
 
 
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  ---
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  # SCFields Release Artifacts
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  This dataset repository contains assets, contact-field datasets, and contact-field checkpoints used by the SCFields release code.
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- Code and project page:
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- - Code: https://github.com/Kevinskwk/SCFields
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- - Project page: https://kevinskwk.github.io/SCFields
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  ## Layout
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@@ -29,7 +35,11 @@ Each checkpoint folder contains:
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  - `model.ckpt`: PyTorch Lightning checkpoint.
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  - `config.yaml`: the accompanying training configuration.
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- ## Download
 
 
 
 
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  ```bash
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  hf download Kevinskwk/scfields-release \
@@ -47,3 +57,30 @@ The release code's `scripts/download_assets.sh` maps shortened hosted asset path
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  assets/peeler_raw -> assets/peeler
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  assets/peeler_combined -> assets/peelers_combined
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: cc-by-nc-4.0
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+ task_categories:
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+ - robotics
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+ tags:
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+ - tactile-sensing
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+ - contact-fields
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+ - manipulation
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  ---
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  # SCFields Release Artifacts
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  This dataset repository contains assets, contact-field datasets, and contact-field checkpoints used by the SCFields release code.
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+ **Paper:** [Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation](https://huggingface.co/papers/2602.13833)
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+ **Project page:** https://kevinskwk.github.io/SCFields
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+ **Code:** https://github.com/Kevinskwk/SCFields
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  ## Layout
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  - `model.ckpt`: PyTorch Lightning checkpoint.
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  - `config.yaml`: the accompanying training configuration.
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+ ## Usage
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+
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+ ### Download
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+
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+ You can use the Hugging Face CLI to download the artifacts:
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  ```bash
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  hf download Kevinskwk/scfields-release \
 
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  assets/peeler_raw -> assets/peeler
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  assets/peeler_combined -> assets/peelers_combined
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  ```
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+
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+ ### Training Example
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+
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+ To train the SCFields policy using the provided dataset and checkpoints, you can use the following command structure:
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+
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+ ```bash
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+ python train.py \
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+ --config-dir=config/scraping_real \
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+ --config-name=contact_field_delta_ee.yaml \
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+ data_root=/path/to/scfields \
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+ task.dataset.dataset_dir=/path/to/scfields/data/real/real_scraper_corrected_lambda1 \
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+ task.dataset.contact_field_checkpoint_path=/path/to/scfields/checkpoints/contact_field/tools_real/model.ckpt
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+ ```
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @misc{ma2026semanticcontactfieldscategorylevelgeneralizable,
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+ title={Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation},
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+ author={Kevin Yuchen Ma and Heng Zhang and Weisi Lin and Mike Zheng Shou and Yan Wu},
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+ year={2026},
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+ eprint={2602.13833},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.RO},
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+ url={https://arxiv.org/abs/2602.13833},
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+ }
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+ ```