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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 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 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 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:35:23.430071Z

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

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  • 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 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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T14:56:33.945280Z digest=sha256:b91dae4438bee81b3c60778a5233833e945e81a2fb1f3ff81eb7e1c9c1e3b2a1

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:db828b1d595f3f55b044cac2731aaa372918dbd8bde983788d9bac627e7502c3

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=sha256:10084854600f590b428d51f9737eeb93aa1c57f91880fb7532b104d874f939c6

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=sha256:03635dcda3f31476aa5473b08932550666ee7ac8f031ca413cd9bd28d161e71f

Observation f6b67b22-195c-4361-a303-4474e869403e · inbound

The Fourth Monocular Depth Estimation Challenge cites this paper.

The Fourth Monocular Depth Estimation Challenge DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T10:35:23.430071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:35:23.430071Z digest=sha256:945049c2c9c7862534584f1f0ecb836dc13b95d115a00f28dc868e83954a1be4

Observation 95899573-2f5d-40eb-9ea5-7b05d99f92f5 · inbound

VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale Recovery cites this paper.

VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale Recovery DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T00:48:21.489798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:48:21.489798Z digest=sha256:3a763ec6d86d45c7033e64eb8baba1bb6396ee2d0d26ca8cd711fb7e309d728e

Observation e43336a7-ef00-400e-b52a-ad6829c3a79e · inbound

Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real World cites this paper.

Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real World DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-15T21:55:06.768611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:55:06.768611Z digest=sha256:17cba9ef4de2cf8c62366b22d7a0466f94226b761ad1873d59cfea6a57b7ff16

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=sha256:5972a12d68dbca4bf0cb3b44ac120af139b47afebc00bb82a809dca445af05c3

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=sha256:1c65f782d7ea99bf705befc0c7686b73e4e7fa83cd3e7b65cd0ddc0c11563e3b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-11T02:07:59.160853Z digest=sha256:b17ffae5b9b012f19fe382ec65cb2799927dfb94ad00891fd5053ed53a0230ed

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T19:27:57.851793Z digest=sha256:ae670b6981e1971d76c901c9b2df0c946c9e7b055a3947a76313675bbe7636bf

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T18:21:15.831853Z digest=sha256:8497c27e86a304feb4d6840369d5874787fd025d330ca6ac1c4d8fd2a59a37f5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T13:23:06.635434Z digest=sha256:e2d04e80a2bbd2ef0b0681c05d03f008b7ced2c5eaa83c6d4af6440bb8b13f40

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T17:49:58.532910Z digest=sha256:7d0a1088858feb3855352fd868e1cddd3b02f79e5a3c0ec3847d7faf086c3c59

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:a3a22352569b040c782f683cdb17ab2c2588f165552a949a1dc692d000f8c4e0

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=sha256:0c0d5e341de1e36f044693dd65a8793ecff767979dded0bfa225b632c436133c