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pith:3XCKCX75

pith:2026:3XCKCX75YHLNQEDAYBBQVC257V
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AdaptSplat: Adapting Vision Foundation Models for Feed-Forward 3D Gaussian Splatting

Mingwei Xing, Xinliang Wang, Yifeng Shi

A single 1.5-million-parameter adapter added to vision foundation models enables superior feed-forward 3D Gaussian Splatting.

arxiv:2605.10239 v2 · 2026-05-11 · cs.CV

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\pithnumber{3XCKCX75YHLNQEDAYBBQVC257V}

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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

introducing a single adapter of only 1.5M parameters into the generic architecture is sufficient to achieve superior performance.

C2weakest assumption

That high-frequency structural priors extracted from shallow features of a vision foundation model backbone can be seamlessly integrated to compensate for low-pass filtering without requiring additional domain-specific fine-tuning or larger training data.

C3one line summary

AdaptSplat adds a lightweight Frequency-Preserving Adapter to vision foundation models that extracts direction-aware high-frequency priors and integrates them via positional encodings and residual modulation to improve feed-forward 3D Gaussian Splatting fidelity and cross-domain performance.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-20T00:04:35.718146Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ddc4a15ffdc1d6d81060c0430a8b5dfd51e1390c5a5d3764c8717067bfb4f021

Aliases

arxiv: 2605.10239 · arxiv_version: 2605.10239v2 · doi: 10.48550/arxiv.2605.10239 · pith_short_12: 3XCKCX75YHLN · pith_short_16: 3XCKCX75YHLNQEDA · pith_short_8: 3XCKCX75
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3XCKCX75YHLNQEDAYBBQVC257V \
  | 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: ddc4a15ffdc1d6d81060c0430a8b5dfd51e1390c5a5d3764c8717067bfb4f021
Canonical record JSON
{
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    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-sa/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-11T09:14:05Z",
    "title_canon_sha256": "4919499c3f803d4a011e7a86b24d5f340a0b04254d5e5ba8747c788cf0127e1c"
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    "kind": "arxiv",
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