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Paper Citation Record · LEDGER

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

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 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 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:06:36.034865Z

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
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  • 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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T14:56:33.945280Z digest=sha256:cc016f76ea9261bc2b940a385cabf66b49fe8cb39fea4289cad1ed0edaf5e05e

Observation ba50e6f6-f75f-43d5-81c1-930477067e63 · inbound

Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching cites this paper.

Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T21:06:36.034865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T21:06:36.034865Z digest=sha256:b4ee903c690d8b646c7d75975d25c12ce8e8ebd181213a8e421991f7e95aa791

Observation 79e2fc14-480a-485a-8b04-acbe4df3dc07 · inbound

Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail cites this paper.

Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T21:29:58.577346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:29:58.577346Z digest=sha256:1543469f4cef3f64855e00919aff6d4d85d6f98e99f245a0dd3110e869c14b19

Observation 899ecfa9-da76-4845-95db-fd153375aa7a · inbound

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking cites this paper.

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T23:16:55.307903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:16:55.307903Z digest=sha256:b5ae8c64868b1e0bb410c824a714c60c37a65ac5f631a028b23dddd3eb444644

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.

source=arxiv_source observed=2026-08-07T13:26:10.240658Z digest=sha256:d0f058d7c03843d857882f0c16d9f94ffaac2fa5e40c6d4dc8dde67794f4d0fe

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.

source=pdf_text observed=2026-08-06T20:52:02.428798Z digest=sha256:78883cf5c926b3766e65b6c8ce371ee0b3468b9fc09fbe2183b67e58512f21af

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-11T02:07:59.160853Z digest=sha256:8e2cc0a3e1c81690b4044021479c49fcef7bc59a426fbb6fa855b27a6bb21020

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T19:27:57.851793Z digest=sha256:9035cafa7eac01cffae5fba44bb5cdee3c83b2c1a3c7f1d8594a00b5bbb4897c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T18:21:15.831853Z digest=sha256:d889fe893460142420cd2cc92d3b9b9e8709818d0f09c9a33b1d517188df94a0

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-30T13:23:06.635434Z digest=sha256:ff44f2939718284d13c769b5aceaddb830bd3acec95568d5fd0a44fffde061da

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-29T17:49:58.532910Z digest=sha256:312b8da84c83c64ca2ae18e356ae2513753afeb31dd23519005bc1cee45cea6e

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.

source=pdf_text observed=2026-08-01T19:07:10.204833Z digest=sha256:d036ca2cc3988715ec83dd980e6ac29ac01f3c325809ada39d14c6fddc6b3740

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.

source=arxiv_source observed=2026-08-04T00:54:27.186641Z digest=sha256:0ea9197b112d8402a898d77d91229a17e9d9dcda5a72185c215d5c3eea253ab4