Pith Number

pith:KLZYZBEQ

pith:2026:KLZYZBEQD4DLL4VTXKPMDVMVYT

not attested not anchored not stored refs resolved

Smart target point control for Gaussian Splatting methods

Andreas Kolb, Pratik Singh Bisht

A quota-governor steers Gaussian splatting to a target point count by 15k iterations by adjusting only existing densification and pruning parameters.

arxiv:2605.16158 v1 · 2026-05-15 · cs.GR

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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

This quota-governor reaches the desired count by 15k iterations without abrupt cutoffs, ensuring that all methods and views receive equal densification and pruning cycles, enabling fairer, capacity-matched evaluation.

C2weakest assumption

That adjusting only the existing densification and opacity-culling hyper-parameters is sufficient to track a quadratic target count trajectory while preserving the standard densification window and cadence without introducing new quality or distribution biases.

C3one line summary

A quota-governor for Gaussian Splatting that tracks a quadratic target point count by adjusting existing hyperparameters, reaching the target by 15k iterations without hard cutoffs for fairer evaluations.

References

11 extracted · 11 resolved · 0 Pith anchors

[1] 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42(4), July 2023 2023

[2] Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106 2021

[3] Instant neural graphics primitives with a multiresolution hash encoding.ACM transactions on graphics (TOG), 41(4):1–15 2022

[4] 2d gaussian splatting for geometrically accurate radiance fields 2024

[5] High-quality surface reconstruction using gaussian surfels 2024

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-20T00:01:55.447402Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

52f38c84901f06b5f2b3ba9ec1d595c4fdf7958d5634ed243592ab16ced35113

Aliases

arxiv: 2605.16158 · arxiv_version: 2605.16158v1 · doi: 10.48550/arxiv.2605.16158 · pith_short_12: KLZYZBEQD4DL · pith_short_16: KLZYZBEQD4DLL4VT · pith_short_8: KLZYZBEQ

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/KLZYZBEQD4DLL4VTXKPMDVMVYT \
  | 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: 52f38c84901f06b5f2b3ba9ec1d595c4fdf7958d5634ed243592ab16ced35113

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "5444bbc21bc321a26fdc5e3ea4ace25e626f959d6496b65df97810d370781a62",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.GR",
    "submitted_at": "2026-05-15T16:38:45Z",
    "title_canon_sha256": "6173354c17a2511b4e1f0f18394190de751e945edf922cb8fb82ab0aa0133518"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16158",
    "kind": "arxiv",
    "version": 1
  }
}