Pith Number

pith:GHV2EPOO

pith:2019:GHV2EPOO33L4JURQD7QDXN4GIT

not attested not anchored not stored refs resolved

The Replica Dataset: A Digital Replica of Indoor Spaces

Anton Clarkson, Brian Budge, Carl Ren, Dhruv Batra, Elias Mueggler, Erik Wijmans, Hauke M. Strasdat, Jakob J. Engel, Jesus Briales, Julian Straub, June Yon, Kimberly Leon, Lingni Ma, Luis Pesqueira, Manolis Savva, Michael Goesele, Mingfei Yan, Nigel Carter, Raul Mur-Artal, Renzo De Nardi, Richard Newcombe, Shobhit Verma, Simon Green, Steven Lovegrove, Thomas Whelan, Tyler Gillingham, Xiaqing Pan, Yajie Yan, Yufan Chen, Yuyang Zou

Replica is a dataset of 18 photo-realistic 3D indoor scenes designed so machine learning models trained on it may work directly on real-world data.

arxiv:1906.05797 v1 · 2019-06-13 · cs.CV · cs.GR · eess.IV

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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

Due to the high level of realism of the renderings from Replica, there is hope that ML systems trained on Replica may transfer directly to real world image and video data.

C2weakest assumption

That the 18 scenes achieve sufficient photo-realism and geometric accuracy in their meshes, textures, and semantics for ML models to transfer directly to real-world data without additional domain adaptation.

C3one line summary

Replica is a new dataset of 18 highly detailed 3D reconstructions of indoor spaces with meshes, high-resolution HDR textures, per-primitive semantics, and mirror/glass reflectors for realistic ML training.

References

28 extracted · 28 resolved · 2 Pith anchors

[1] On Evaluation of Embodied Navigation Agents 2018 · arXiv:1807.06757

[2] Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments 2018

[3] Lawrence Zitnick, and Devi Parikh 2015

[4] Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese 2016

[5] Ptex: Per-face texture mapping for production rendering 2008

Cited by

115 papers in Pith

Image2Sim: Scaling Embodied Navigation via Generative Neural Simulator

PUF: Plug-and-Play Uncertainty-Aware Fusion for Online 3D Scene Graph Generation

GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM

GUSH3R: Everyone Everywhere All at Once as Gaussians

Beyond Isolated Objects: Relationship-aware Open Vocabulary Scene Understanding via 3D Scene Graph Analysis

Receipt and verification

First computed	2026-07-04T23:42:36.288162Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

31eba23dceded7c4d2301fe03bb78644fd4aa471bd1f245572b052f5a8f7cc67

Aliases

arxiv: 1906.05797 · arxiv_version: 1906.05797v1 · doi: 10.48550/arxiv.1906.05797 · pith_short_12: GHV2EPOO33L4 · pith_short_16: GHV2EPOO33L4JURQ · pith_short_8: GHV2EPOO

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/GHV2EPOO33L4JURQD7QDXN4GIT \
  | 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: 31eba23dceded7c4d2301fe03bb78644fd4aa471bd1f245572b052f5a8f7cc67

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "63e7bd12d729040b94aa7f4d1d4a20bac7dfbd91ff82ebba8f04895c43a37a70",
    "cross_cats_sorted": [
      "cs.GR",
      "eess.IV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2019-06-13T16:29:58Z",
    "title_canon_sha256": "48f79c72631ba15ec744218404a71a12861a0bef7b75328a49a7622e4aa5e0ef"
  },
  "schema_version": "1.0",
  "source": {
    "id": "1906.05797",
    "kind": "arxiv",
    "version": 1
  }
}