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pith:W2K32ELX

pith:2026:W2K32ELX6THYJMYEALR375CR2V
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OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention

Federico Tombari, Kunyi Li, Michael Niemeyer, Nassir Navab, Sen Wang, Stefano Gasperini

OpenGaFF models semantics as a continuous function of 3D Gaussian geometry to achieve spatially coherent open-vocabulary scene understanding.

arxiv:2605.06088 v2 · 2026-05-07 · cs.CV

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\pithnumber{W2K32ELX6THYJMYEALR375CR2V}

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1 Bitcoin timestamp
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

Extensive experiments on standard 2D and 3D open-vocabulary benchmarks demonstrate that our method consistently outperforms prior approaches, achieving improved segmentation quality, stronger 3D semantic consistency and a semantically interpretable codebook that provides insight into the learned representation.

C2weakest assumption

That explicitly conditioning semantic predictions on geometric structure will strengthen the coupling between geometry and semantics and thereby improve spatial coherence across similar structures in 3D space.

C3one line summary

OpenGaFF combines a geometry-conditioned Gaussian Feature Field with codebook-guided attention to deliver more spatially coherent open-vocabulary 3D semantic segmentation than prior methods.

Receipt and verification
First computed 2026-05-20T00:02:12.429994Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

b695bd1177f4cf84b30402e3bff451d55b6510f46679fd39ed29bd1ed90ba1fd

Aliases

arxiv: 2605.06088 · arxiv_version: 2605.06088v2 · doi: 10.48550/arxiv.2605.06088 · pith_short_12: W2K32ELX6THY · pith_short_16: W2K32ELX6THYJMYE · pith_short_8: W2K32ELX
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/W2K32ELX6THYJMYEALR375CR2V \
  | 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: b695bd1177f4cf84b30402e3bff451d55b6510f46679fd39ed29bd1ed90ba1fd
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "a43211dbf562e4f3cb60c1b1efbb12d14d3e5b2e8b143f0b81030cb329a23e4a",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-07T12:10:07Z",
    "title_canon_sha256": "3a7aa2b7f22f1ffae4a17cc0ef6fabd51c3e11955671f4404542581da69ff021"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.06088",
    "kind": "arxiv",
    "version": 2
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}