Pith Number

pith:2RLAJPX5

pith:2026:2RLAJPX55BQI5AOFWRWE6E2KBX

not attested not anchored not stored refs pending

ViPS: Video-informed Pose Spaces for Auto-Rigged Meshes

Ayush Tewari, Changxi Zheng, Honglin Chen, Karran Pandey, Matheus Gadelha, Niloy J. Mitra, Paul Guerrero, Rundi Wu, Yannick Hold-Geoffroy

Video diffusion priors can be distilled into a universal, controllable pose space for arbitrary auto-rigged meshes that matches models trained on synthetic 4D data and generalizes zero-shot to new species and skeletal topologies.

arxiv:2604.17623 v3 · 2026-04-19 · cs.CV · cs.GR

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\usepackage{pith}
\pithnumber{2RLAJPX55BQI5AOFWRWE6E2KBX}

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

ViPS, trained solely on video priors, matches the performance of state-of-the-art methods trained on synthetic artist-created 4D data in both plausibility and diversity. Most importantly, as a universal model, ViPS demonstrates robust zero-shot generalization to out-of-distribution species and unseen skeletal topologies.

C2weakest assumption

That motion priors encoded in a pretrained 2D video diffusion model can be reliably transferred into a universal distribution over arbitrary rig parameters, and that differentiable geometric validators applied to the skinned mesh are sufficient to enforce asset-specific validity without manual regularizers.

C3one line summary

ViPS distills a compact, controllable distribution of valid joint configurations for any auto-rigged mesh from video diffusion priors, matching 4D-trained methods in plausibility while generalizing zero-shot to unseen species and skeletal topologies.

Receipt and verification

First computed	2026-05-22T01:03:19.403145Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d45604befde8608e81c5b46c4f134a0df1871a6e8612d3ff42f3f2125b1f1556

Aliases

arxiv: 2604.17623 · arxiv_version: 2604.17623v3 · doi: 10.48550/arxiv.2604.17623 · pith_short_12: 2RLAJPX55BQI · pith_short_16: 2RLAJPX55BQI5AOF · pith_short_8: 2RLAJPX5

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2RLAJPX55BQI5AOFWRWE6E2KBX \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d45604befde8608e81c5b46c4f134a0df1871a6e8612d3ff42f3f2125b1f1556

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "cab60c5b1f8e321e505f23d23648ba6a3bb111f931a177ffd25fc920b62dac05",
    "cross_cats_sorted": [
      "cs.GR"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-19T21:21:11Z",
    "title_canon_sha256": "0d6382544663b3dd8b79537e51536b403de27da2d8090fc5025da006515649c1"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.17623",
    "kind": "arxiv",
    "version": 3
  }
}