Paper Citation Record · LEDGER

DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2110.11590.

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

pith.paper-citation-record.v1
2110.11590 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:26:10.240658Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:24:39.991107Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 8b54f2d0-a0b7-423f-ae01-315ce3485b89 · inbound

Depth Anything V2 cites this paper.

Depth Anything V2 DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T14:56:34.152838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a97665bb-a4fb-417c-a83b-b4de7097d29d · inbound

Collaborative Learning for Unsupervised Multimodal Remote Sensing Image Registration: Integrating Self-Supervision and MIM-Guided Diffusion-Based Image Translation cites this paper.

Collaborative Learning for Unsupervised Multimodal Remote Sensing Image Registration: Integrating Self-Supervision and MIM-Guided Diffusion-Based Image Translation DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:10.240658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372d1716-56b9-4012-b9c6-aae12951e38d · inbound

Depth Anything at Any Condition cites this paper.

Depth Anything at Any Condition DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T20:52:02.428798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fce2d46a-3173-4357-9afb-7e84fcb3c3c0 · inbound

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

Depth Anything 3: Recovering the Visual Space from Any Views DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:07:59.239450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7b5996b3-c44e-405e-b8cb-9fa7f3edcd84 · inbound

Multi-Order Matching Network for Alignment-Free Depth Super-Resolution cites this paper.

Multi-Order Matching Network for Alignment-Free Depth Super-Resolution DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-21T19:30:31.442361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79b41be6-fd70-4f26-92a0-8bea712d028b · 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 DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:24:18.300894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96f7cb45-f2c2-473a-bded-9c3166c4d29a · inbound

Vision-Guided Outdoor Flight and Obstacle Evasion via Reinforcement Learning cites this paper.

Vision-Guided Outdoor Flight and Obstacle Evasion via Reinforcement Learning DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:24:39.992595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 83db390d-5752-4f8f-9c88-8fcbbd49eecd · inbound

SpatialBench: Is Your Spatial Foundation Model an All-Round Player? cites this paper.

SpatialBench: Is Your Spatial Foundation Model an All-Round Player? DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-29T17:53:47.261605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b461072-abed-4860-b80d-8fa59d84f493 · inbound

DepthART: Scaling Foundation Monocular Depth to Tiny Models cites this paper.

DepthART: Scaling Foundation Monocular Depth to Tiny Models DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T19:07:10.204833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc2333f3-e486-45a5-81ce-9203d1f641f6 · inbound

Breaking the Horizontal Prior: From Long-Tailed Orientation Bias to Roll-Robust Monocular Depth Estimation cites this paper.

Breaking the Horizontal Prior: From Long-Tailed Orientation Bias to Roll-Robust Monocular Depth Estimation DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T00:54:27.186641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.