Paper Citation Record · LEDGER

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

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 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 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:42:27.776029Z

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

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verified exact0
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 594b5a29-9372-49b8-9285-d13b5945fb35 · inbound

AutoML: A Survey of the State-of-the-Art cites this paper.

AutoML: A Survey of the State-of-the-Art IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-14T15:38:07.529775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

Observation 615781d9-6354-474f-9e8a-5080f3801dba · inbound

Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots cites this paper.

Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots 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 2026-08-15T16:42:27.776029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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.

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.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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.

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.

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

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

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.

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.