Pith Number

pith:GNVTFQQ7

pith:2025:GNVTFQQ76FBSQI4GJXYGE632OJ

not attested not anchored not stored refs resolved

Make-It-Poseable: Feed-forward Latent Posing Model for 3D Characters

Alan Zhao, Houqiang Li, Jax Xiang, Ori Zhang, Wengang Zhou, Zhenxun Yuan, Zhiyang Guo

Make-It-Poseable poses 3D characters by transforming compact latent representations instead of meshes or skinning weights.

arxiv:2512.16767 v2 · 2025-12-18 · cs.CV

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2 Internet Archive

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

our method significantly outperforms existing baselines in posing quality. Furthermore, our skeleton-agnostic design exhibits remarkable zero-shot generalization to diverse morphologies including quadrupeds and seamlessly supports various 3D authoring applications such as part replacement and refinement.

C2weakest assumption

That operating directly on compact latent representations can faithfully reconstruct fine geometric details and handle arbitrary topological changes without introducing artifacts or requiring mesh-specific priors.

C3one line summary

A latent-space transformer framework poses 3D characters without skinning or fixed topologies, outperforming baselines and generalizing zero-shot to quadrupeds.

References

51 extracted · 51 resolved · 3 Pith anchors

[1] Adobe. Mixamo, 2024.https://www.mixamo.com. 6 2024

[2] Automatic rigging and ani- mation of 3D characters.ACM TOG, 26(3):72–es, 2007 2007

[3] Human- Rig: Learning automatic rigging for humanoid character in a large scale dataset, 2024 2024

[4] DetailGen3D: Generative 3D geometry enhancement via data-dependent flow, 2025 2025

[5] Anymate: A dataset and baselines for learning 3D object rigging 2025

Cited by

1 paper in Pith

AniGen: Unified $S^3$ Fields for Animatable 3D Asset Generation

Receipt and verification

First computed	2026-05-18T02:44:32.096188Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

336b32c21ff1432823864df0627b7a726fd7b0103b1455a4e95127cee8be380e

Aliases

arxiv: 2512.16767 · arxiv_version: 2512.16767v2 · doi: 10.48550/arxiv.2512.16767 · pith_short_12: GNVTFQQ76FBS · pith_short_16: GNVTFQQ76FBSQI4G · pith_short_8: GNVTFQQ7

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GNVTFQQ76FBSQI4GJXYGE632OJ \
  | 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: 336b32c21ff1432823864df0627b7a726fd7b0103b1455a4e95127cee8be380e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "ce7d254e428bd6ce8872455b89d0a5fc91fc4fc273cad9279ab5ee6956360877",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-12-18T17:01:44Z",
    "title_canon_sha256": "a990cfbf2a0a213047ee334957de12579302c365ff6412bb63403ffca9b7abe2"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2512.16767",
    "kind": "arxiv",
    "version": 2
  }
}