pith:W2K32ELX
OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention
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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Record completeness
Claims
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.
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.
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
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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
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