pith:MAZWOIL5
DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tiles
Diffusion priors and active view sampling let Gaussian Splatting Wang Tiles be built from minimal observations while preserving quality.
arxiv:2602.15355 v4 · 2026-02-17 · cs.CV
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\usepackage{pith}
\pithnumber{MAZWOIL5Z62F4FVYO72FXZAJVG}
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Record completeness
Claims
our system significantly reduces the required data volume while maintaining the visual integrity and interactive performance necessary for large-scale virtual environments
That diffusion models can reliably hallucinate missing structural details in a way that produces seamless tile transitions without visible artifacts or inconsistencies across boundaries.
DAV-GSWT uses diffusion priors and active view sampling to synthesize high-fidelity Gaussian Splatting Wang Tiles from minimal observations while preserving visual quality and tile transitions.
Receipt and verification
| First computed | 2026-07-23T00:23:38.603709Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
603367217dcfb45e16b877f45be409a9b482e986fd0bda5d4f3e492ccd3b5438
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MAZWOIL5Z62F4FVYO72FXZAJVG \
| 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: 603367217dcfb45e16b877f45be409a9b482e986fd0bda5d4f3e492ccd3b5438
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2026-02-17T04:47:39Z",
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