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Paper Citation Record · LEDGER

IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:1912.09678.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1912.09678 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:49:49.614348Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-08T02:04:26.375141Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1e3209bd-be31-471c-8321-c58d428d164d · inbound

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth cites this paper.

ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 43

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verified exact
arxiv_id, observed 2026-05-14T22:12:47.172426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b4f33f18-4698-495b-95c2-2eb9e4b2e5c2 · inbound

MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details cites this paper.

MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 59

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verified exact
arxiv_id, observed 2026-05-14T21:19:44.233684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b63e5b4c-47cf-4782-8ddc-43eac02e852b · inbound

Depth Anything 3: Recovering the Visual Space from Any Views cites this paper.

Depth Anything 3: Recovering the Visual Space from Any Views IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 93

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verified exact
arxiv_id, observed 2026-05-11T02:07:59.242963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 72779c9e-5552-4a31-8733-47b0f131b48e · inbound

Lite Any Stereo: Efficient Zero-Shot Stereo Matching cites this paper.

Lite Any Stereo: Efficient Zero-Shot Stereo Matching IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 54

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verified exact
arxiv_id, observed 2026-05-17T20:32:04.993307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-17T20:31:18.887589Z digest=sha256:f04369871967ec7218040a743b2530f537a43a700dd46baa465d192139241654

Observation c1f392ca-0470-4157-a179-d90c3bc689f2 · inbound

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model cites this paper.

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 50

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verified exact
arxiv_id, observed 2026-05-21T18:24:18.276749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T18:21:15.831853Z digest=sha256:00f114aaf2f91b2b0c698aa1796f05eb9377bb275b6deff13e8179ade08b59df

Observation 985702a3-982d-4a17-a7d6-9b2e4b3c31aa · inbound

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources cites this paper.

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 108

Resolution
unresolved
no resolver link, observed 2026-08-03T06:50:26.811842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:50:26.811842Z digest=sha256:99afc27a0b1990d33100db3bbecc0adc82af87b3c1e9fa36645494983d0c3a19

Observation 94be99cc-5057-4367-ac23-5f8f403aa7ae · inbound

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction cites this paper.

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 82

Resolution
unresolved
no resolver link, observed 2026-07-13T21:45:59.210064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T21:45:59.210064Z digest=sha256:206bc5f410fc34a1d0f7b67b487a8c643f9c7da3d0e8a5970e837c0bd359d170

Observation db4f1a95-e960-454f-ba98-a50f9a257106 · inbound

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth cites this paper.

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:11:25.311920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 96ddb9ac-0056-4f47-8214-1c7eaa174e11 · inbound

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth cites this paper.

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T07:52:32.243767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2de77c41-7ac7-4586-9ab5-28d6c962ae6e · inbound

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth cites this paper.

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:27:59.552088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-14T21:27:45.071498Z digest=sha256:33be62bdacf094a9435841eb7f88a50c4187260948c9396fc966225f5d181ebc

Observation 6ce29bec-f957-4262-89fe-af4c032facf6 · inbound

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth cites this paper.

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T23:03:50.753981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T23:00:25.109961Z digest=sha256:bb4ede744eec2ae27f500271641ae92b25ea242c3cf1d0d1b98e60201f29daf1

Observation 8797cce1-2766-48ef-b11c-ff541d62e450 · inbound

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images cites this paper.

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:58:02.596145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T09:47:25.510821Z digest=sha256:1ead17322368769a5655aaa88a19c6ebd69454d6acbf254f2cb95f0c1d462a34

Observation 2f78c13d-6bce-4491-9cef-48f2f4465853 · inbound

Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching cites this paper.

Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:39:57.482969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T00:24:59.443792Z digest=sha256:c819f505a8cd7d99413a7080118ab3258b4e69a4c359a356fbe6ae6065c778ff

Observation 39e09c79-ed66-41d8-ad82-e097c63f3c44 · inbound

Vision as Unified Multimodal Generation cites this paper.

Vision as Unified Multimodal Generation IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 180

Resolution
verified exact
local_arxiv, observed 2026-07-08T02:04:26.377005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-08T01:54:30.649092Z digest=sha256:3460c50fd97c41a6a530e8eab0c82f12671a0b34b9b6174cc23c925ce64f894c

Observation 1cc18ed6-a08d-447a-a829-61293dc38e1e · inbound

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement cites this paper.

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-01T16:34:24.074940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:34:24.074940Z digest=sha256:3fa57a586a6b12cd534f97dfd4c57cb6b593ff11ba58c6aa37d24180e5eadcea

Observation 95644c88-a683-4e5e-b9b8-8c1a3bba4da3 · inbound

GeoStereo: A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal cites this paper.

GeoStereo: A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 62

Resolution
unresolved
no resolver link, observed 2026-07-31T23:18:22.194895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8d4a6a0f-efba-4b16-8533-01d2b79af448 · inbound

GeoStereo: A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal cites this paper.

GeoStereo: A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-04T03:48:29.814752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0b65de0a-1feb-49ec-bf60-95838f17b5a6 · inbound

Dense Metric Depth Completion from Sparse Direct Time-of-Flight Sensors cites this paper.

Dense Metric Depth Completion from Sparse Direct Time-of-Flight Sensors IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T17:49:49.614348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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