Pith Number

pith:2KSQKR5G

pith:2024:2KSQKR5GVKHBAYN32RKDAAYYRJ

not attested not anchored not stored refs resolved

Structured 3D Latents for Scalable and Versatile 3D Generation

Bowen Zhang, Dong Chen, Jianfeng Xiang, Jiaolong Yang, Ruicheng Wang, Sicheng Xu, Xin Tong, Yu Deng, Zelong Lv

A structured latent that merges sparse 3D grids with dense multiview features supports high-quality generation of 3D assets in multiple output formats from text or image input.

arxiv:2412.01506 v3 · 2024-12-02 · cs.CV

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\usepackage{pith}
\pithnumber{2KSQKR5GVKHBAYN32RKDAAYYRJ}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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 model generates high-quality results with text or image conditions, significantly surpassing existing methods, including recent ones at similar scales.

C2weakest assumption

The integration of a sparsely-populated 3D grid with dense multiview visual features from a vision foundation model comprehensively captures both structural geometry and textural appearance information while maintaining decoding flexibility.

C3one line summary

SLAT provides a unified 3D latent representation enabling versatile high-quality generation across multiple output formats from text or image inputs.

References

117 extracted · 117 resolved · 6 Pith anchors

[1] Gpt-4o system card. 2024. 6, 16 2024

[2] GPT-4 Technical Report 2023 · arXiv:2303.08774

[3] Build- ing normalizing flows with stochastic interpolants

[4] Improving image generation with better captions 2023

[5] Demystifying mmd gans 2018

Formal links

2 machine-checked theorem links

Cited by

36 papers in Pith

GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction

Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

Art3D: Training-Free 3D Generation from Flat-Colored Illustration

PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects

SVG360: Editable Multiview Vector Graphics from a Single SVG

Receipt and verification

First computed	2026-05-17T23:38:47.485867Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d2a50547a6aa8e1061bbd4543003188a5b606ad9a09f52e95f342425d0d1088b

Aliases

arxiv: 2412.01506 · arxiv_version: 2412.01506v3 · doi: 10.48550/arxiv.2412.01506 · pith_short_12: 2KSQKR5GVKHB · pith_short_16: 2KSQKR5GVKHBAYN3 · pith_short_8: 2KSQKR5G

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2KSQKR5GVKHBAYN32RKDAAYYRJ \
  | 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: d2a50547a6aa8e1061bbd4543003188a5b606ad9a09f52e95f342425d0d1088b

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "96be00091563b2de602b346b0c76a70c54d96c9ef69bb79de500a8ce3b3b2b68",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2024-12-02T13:58:38Z",
    "title_canon_sha256": "443f06edc7fa6690c52d391606e40ad8d719a0f4504a7a26de7b2284a959bdea"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2412.01506",
    "kind": "arxiv",
    "version": 3
  }
}