Pith Number

pith:A7LECMVZ

pith:2026:A7LECMVZOTUQX6SSWFH3QGZK6L

not attested not anchored not stored refs resolved

LEXI-SG: Monocular 3D Scene Graph Mapping with Room-Guided Feed-Forward Reconstruction

Ayoung Kim, Christina Kassab, Hyeonjae Gil, Mat\'ias Mattamala, Maurice Fallon

Monocular RGB alone can build accurate dense open-vocabulary 3D scene graphs when rooms guide reconstruction order and global alignment.

arxiv:2605.13741 v1 · 2026-05-13 · cs.RO · cs.CV

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{A7LECMVZOTUQX6SSWFH3QGZK6L}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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

LEXI-SG is the first dense monocular visual mapping system for open-vocabulary 3D scene graphs using only RGB camera input, achieving improved trajectory estimation and dense reconstruction on indoor scenes.

C2weakest assumption

The method assumes that open-vocabulary foundation models can reliably partition the scene into rooms and that deferring reconstruction until each room is fully observed will eliminate scale inconsistencies without introducing other drift or alignment errors.

C3one line summary

LEXI-SG is the first monocular RGB system for dense open-vocabulary 3D scene graphs that partitions scenes into rooms and performs feed-forward reconstruction per room before global factor-graph alignment.

References

35 extracted · 35 resolved · 2 Pith anchors

[1] Hierarchical Open-V ocabulary 3D Scene Graphs for Language-Grounded Robot Navigation, 2024

[2] ConceptGraphs: Open-V ocabulary 3D Scene Graphs for Perception and Planning, 2024

[3] Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs, 2021

[4] OpenMask3D: Open-V ocabulary 3D Instance Segmentation, 2023

[5] Clio: Real-time Task-Driven Open-Set 3D Scene Graphs, 2024

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T02:44:16.457818Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

07d64132b974e90bfa52b14fb81b2af2f9eeb0a9655878bf051a4e6c54499d74

Aliases

arxiv: 2605.13741 · arxiv_version: 2605.13741v1 · doi: 10.48550/arxiv.2605.13741 · pith_short_12: A7LECMVZOTUQ · pith_short_16: A7LECMVZOTUQX6SS · pith_short_8: A7LECMVZ

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/A7LECMVZOTUQX6SSWFH3QGZK6L \
  | 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: 07d64132b974e90bfa52b14fb81b2af2f9eeb0a9655878bf051a4e6c54499d74

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "96aa172512f0f59321b279da85f40eb4edd9720e99f7e3b102075d28683093e0",
    "cross_cats_sorted": [
      "cs.CV"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-13T16:19:02Z",
    "title_canon_sha256": "cce0fc904d3179fbe85bf7d372737fede9c5d435a77aec2bbcdd43ed408c0a00"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13741",
    "kind": "arxiv",
    "version": 1
  }
}