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DigitCode: Symbolic Tokenization of Hand Motion by Anatomical Units — arXiv:2608.03127

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.03127
License (as archived): CC0-1.0
Archived: 2026-10-31T12:18:35.363Z
SHA-256 of the archived text: d3261c69dde3c4129b594cd2514db337ac514dc38752220f419ab5cbecf13bbf
Stable URL of this page: https://metraipolis.com/documento/dc_a019ba2ef46c

How to cite

DigitCode: Symbolic Tokenization of Hand Motion by Anatomical Units — arXiv:2608.03127 — arXiv (en), https://arxiv.org/abs/2608.03127 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_a019ba2ef46c (Metraipolis archive dc_a019ba2ef46c, sha256 d3261c69dde3c4129b594cd2514db337ac514dc38752220f419ab5cbecf13bbf)

BibTeX

@misc{dca019ba2ef46c,
  title = {DigitCode: Symbolic Tokenization of Hand Motion by Anatomical Units — arXiv:2608.03127},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.03127},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_a019ba2ef46c; sha256 d3261c69dde3c4129b594cd2514db337ac514dc38752220f419ab5cbecf13bbf},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.03127. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Hand motion carries the finest-grained information in human activity, yet the representations behind hand generation, understanding, and robot learning are overwhelmingly continuous--joint angles or MANO parameters. These are accurate but unstructured: a finger cannot be indexed or edited as a symbol, and nothing marks a pose as anatomically valid. Discrete symbolic representations supply exactly this structure, and Hand Labanotation (HL) has shown they are feasible for the hand, writing motion as a T x 40 grid of one fixed direction symbol per bone. Building on this grid, we ask the question underneath it: the anatomical unit a symbol should span--bone, finger, or whole hand. DigitCode answers it by adapting, grouping, and layering HL's alphabet along the hand's unit hierarchy within one code, cutting the symbolic representation's quantization error by three quarters. The lever is the unit, not the quantizer family: at a fixed unit, training-free and learned strong quantizers are interchangeable on reconstruction, while moving down the anatomical hierarchy is what shifts accuracy. The hierarchy also tracks what downstream tasks need. Because a finger is a genuine, enumerable unit, one per-finger token doubles as a training-free, editable handle for jobs a continuous representation cannot address--repairing malformed generated hands, and retargeting them onto robots. We release HandTok, a reproducible testbed, so hand tokenizers can be compared unit-for-unit. Project page: this https URL .

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-05 in cs.AI).
Categorie arXiv: Robotics (cs.RO) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2608.03127 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-31T12:05:53.002Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-05?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).