HandWM

Everything needed to run the HandWM code (hand motion → simulated glove IMU) and the P3-WAM + IMU re-implementation on EgoDex and ARCTIC: the datasets, MANO, intermediate assets and both code trees. organize.sh turns a download into the directory layout the code expects; see ORGANIZE.md.

hf download RunyiY/HandWM --repo-type dataset --local-dir handwm_download
bash handwm_download/organize.sh handwm_download /path/to/root

Contents

Path	Size	What
data/egodex/<part>/*.tar	2.11 TB	EgoDex, all 338,234 episodes (.hdf5 poses + .mp4 video), ~10 GB tar shards; members are paths relative to raw/egodex
data/arctic/images_zips/sXX/*.zip	696 GB	ARCTIC images, 339 sequences, 10 subjects (s03 is the official test subject, no public annotations)
data/arctic/arctic_unpacked.tar	0.8 GB	ARCTIC raw_seqs (MANO, SMPL-X, object, egocentric camera; 301 sequences), meta, splits_json, mano_v1_2
data/mano/MANO_{LEFT,RIGHT}.pkl	10 MB	MANO v1.2 hand models, chumpy-free copies loadable with smplx
data/p3wam/egodex_mano.tar	23 GB	MANO fits of 162,836 EgoDex episodes (P3-WAM hand targets)
data/p3wam/codec_v2/codec.pt	42 MB	frozen action codec (P3-WAM)
data/p3wam/imu-stage-low/new_params.pt	2.2 GB	IMU warm-up weights for the low-noise expert (train_wam.py --init-new)
code/handswm, code/p3wam_imu	<0.2 GB	code, configs, tests, docs, evaluation results
manifest/		egodex_index.csv.gz (file → shard), egodex_fitted_files.txt (P3-WAM training subset), files.csv.gz (sha256 of every payload file)
data/*/receipts/		download receipts of the original archives

Not included: the Wan2.2-Fun-A14B-Control backbone (Apache-2.0, organize.sh downloads it from alibaba-pai/Wan2.2-Fun-A14B-Control), simulated IMU and canonical motion (regenerated by the code), training checkpoints.

Licenses

Each component keeps its upstream license. All of them are non-commercial.

Component	License	Source
EgoDex	CC BY-NC-ND 4.0, files unchanged (repackaged into tar archives only)	Apple, https://github.com/apple-aiml-research/ml-egodex
ARCTIC (images, annotations, meta)	ARCTIC Data & Software license, non-commercial scientific research	https://arctic.is.tue.mpg.de
MANO models	MANO license, non-commercial scientific research	https://mano.is.tue.mpg.de
EgoDex MANO fits	derived from EgoDex and MANO; their terms apply	this work
Code, codec and IMU weights	research use	this work

Before using ARCTIC or MANO, register and accept their licenses on the sites above.

References

• EgoDex: R. Hoque et al., EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video, 2025.
• ARCTIC: Z. Fan et al., ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation, CVPR 2023.
• MANO: J. Romero, D. Tzionas, M. J. Black, Embodied Hands: Modeling and Capturing Hands and Bodies Together, SIGGRAPH Asia 2017.
• P3-WAM: https://p3-wam.pages.dev/