The dataset could not be loaded because the splits use different data file formats, which is not supported. Read more about the splits configuration. Click for more details.
Error code: FileFormatMismatchBetweenSplitsError
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SCFields Release Artifacts
This dataset repository contains assets, contact-field datasets, and contact-field checkpoints used by the SCFields release code.
Paper: Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation
Project page: https://kevinskwk.github.io/SCFields Code: https://github.com/Kevinskwk/SCFields
Layout
assets/tools: generated TacSL tool assets.assets/peeler_raw: raw original peeler assets.assets/peeler_combined: combined peeler assets.data/sim/tools: simulated contact-field data for tools (tools_mixed).data/sim/peelers: simulated contact-field data for peelers (peelers_combined_new).data/real/scraper: converted real scraper contact-field data (real_scraper_corrected_lambda1).checkpoints/contact_field/tools_sim: tool contact-field checkpoint pretrained on simulated data.checkpoints/contact_field/tools_real: tool contact-field checkpoint finetuned on real data.checkpoints/contact_field/peelers_sim: peeler contact-field checkpoint pretrained on simulated data.checkpoints/contact_field/peelers_real: peeler contact-field checkpoint finetuned on real data.
Each checkpoint folder contains:
model.ckpt: PyTorch Lightning checkpoint.config.yaml: the accompanying training configuration.
Usage
Download
You can use the Hugging Face CLI to download the artifacts:
hf download Kevinskwk/scfields-release \
--repo-type dataset \
--include "assets/**" \
--include "data/sim/**" \
--include "data/real/scraper/**" \
--include "checkpoints/contact_field/**" \
--local-dir /path/to/scfields
The release code's scripts/download_assets.sh maps shortened hosted asset paths to the repo-local asset layout expected by IsaacGym:
assets/peeler_raw -> assets/peeler
assets/peeler_combined -> assets/peelers_combined
Training Example
To train the SCFields policy using the provided dataset and checkpoints, you can use the following command structure:
python train.py \
--config-dir=config/scraping_real \
--config-name=contact_field_delta_ee.yaml \
data_root=/path/to/scfields \
task.dataset.dataset_dir=/path/to/scfields/data/real/real_scraper_corrected_lambda1 \
task.dataset.contact_field_checkpoint_path=/path/to/scfields/checkpoints/contact_field/tools_real/model.ckpt
Citation
@misc{ma2026semanticcontactfieldscategorylevelgeneralizable,
title={Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation},
author={Kevin Yuchen Ma and Heng Zhang and Weisi Lin and Mike Zheng Shou and Yan Wu},
year={2026},
eprint={2602.13833},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2602.13833},
}
- Downloads last month
- 22