Paper Citation Record · LEDGER

What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2403.06090.

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

pith.paper-citation-record.v1
2403.06090 v4

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measured 0 of 0 reference resolution

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measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:27:02.467759Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:02.612683Z

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Outbound references

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Pith citing papers

Observation 5d4661db-3522-411e-a006-891d819ec6fa · inbound

Depth Anything V2 cites this paper.

Depth Anything V2 What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-13T14:56:34.130327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f965914a-7220-4267-9906-f7e0efeecab8 · inbound

DepthMaster: Taming Diffusion Models for Monocular Depth Estimation cites this paper.

DepthMaster: Taming Diffusion Models for Monocular Depth Estimation What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:12:38.903996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f86c6d6d-b3ec-46ac-b464-1e86fb800805 · inbound

UniGeo: Taming Video Diffusion for Unified Consistent Geometry Estimation cites this paper.

UniGeo: Taming Video Diffusion for Unified Consistent Geometry Estimation What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T12:27:02.467759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1ba2654-4f90-4ae8-9634-1490e42c5067 · inbound

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation cites this paper.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T22:41:25.195006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e14575a5-c5c5-4ba1-a698-7c0228fb8a80 · inbound

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? cites this paper.

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:57.550913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fd770d9-716b-444a-b7dc-12a0205fbde5 · inbound

SDMatte: Grafting Diffusion Models for Interactive Matting cites this paper.

SDMatte: Grafting Diffusion Models for Interactive Matting What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T10:15:06.000307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa47d178-3432-49af-9643-c7b103104a63 · inbound

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering cites this paper.

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:21:53.198614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 985c5862-ed81-48ef-bd6f-b9e7f7c4d66e · inbound

LuxDiT: Lighting Estimation with Video Diffusion Transformer cites this paper.

LuxDiT: Lighting Estimation with Video Diffusion Transformer What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T10:52:02.278327Z

Source-reported events for the cited work

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Observation 7c332c6c-75e2-44f3-aa97-bdfadf362410 · inbound

FUMO: Prior-Modulated Diffusion for Single Image Reflection Removal cites this paper.

FUMO: Prior-Modulated Diffusion for Single Image Reflection Removal What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-13T22:15:10.917455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38155c00-39e8-423c-8cf9-2ed1d6450989 · inbound

CDPR: Cross-modal Diffusion with Polarization for Reliable Monocular Depth Estimation cites this paper.

CDPR: Cross-modal Diffusion with Polarization for Reliable Monocular Depth Estimation What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:56:04.138678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd51262d-67da-44ff-9cc0-af5ce1a8b968 · inbound

Monocular Depth Estimation via Neural Network with Learnable Algebraic Group and Ring Structures cites this paper.

Monocular Depth Estimation via Neural Network with Learnable Algebraic Group and Ring Structures What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:41:16.623048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e4f3c02e-8244-4137-bc43-13035072634b · inbound

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors cites this paper.

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 104

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:26:08.021361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d39d7a4e-ab1f-469a-9d52-738e307c95f5 · inbound

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

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:58:02.613988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 64ed51e6-d0c9-4f56-a951-3dd25452ebe9 · inbound

UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception cites this paper.

UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:44:19.330406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 42693fa6-4d01-4555-92e0-54024d796a93 · inbound

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction cites this paper.

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:24:19.407136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c9d9c9a-dc14-4c5b-ba19-d24d263be397 · inbound

Video Generation Models are General-Purpose Vision Learners cites this paper.

Video Generation Models are General-Purpose Vision Learners What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-13T00:56:18.867382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfb43521-67d6-4d4f-9e9c-c24acb63d4d7 · inbound

Unified Video Dense Prediction from Disjoint Data cites this paper.

Unified Video Dense Prediction from Disjoint Data What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-01T07:03:35.462630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.