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Paper Citation Record · LEDGER

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.21034.

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

pith.paper-citation-record.v1
2506.21034 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:41:25.797696Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eaaa942b-9446-4ae1-b367-e79758703fe4 · outbound

This paper cites Tode-trans: Transparent object depth es- timation with transformer.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Tode-trans: Transparent object depth es- timation with transformer

Reference 1

Resolution
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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2fc7222e-a9f0-4259-a714-f87efd07a808 · outbound

This paper cites Clearpose: Large-scale trans- parent object dataset and benchmark.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Clearpose: Large-scale trans- parent object dataset and benchmark

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2dfc50ce-dd1c-4e13-9b47-1b1d930ebeb2 · outbound

This paper cites Domain randomization- enhanced depth simulation and restoration for perceiving and grasping specular and transparent objects.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Domain randomization- enhanced depth simulation and restoration for perceiving and grasping specular and transparent objects

Reference 3

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Observation 6696e375-968c-466c-bae6-d573f9a91a6c · outbound

This paper cites Exploiting the signal-leak bias in diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Exploiting the signal-leak bias in diffusion models

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation bef8b3e2-dc35-46b4-b0aa-2d325ddb92ef · outbound

This paper cites Transcg: A large-scale real-world dataset for transparent object depth completion and a grasping baseline.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Transcg: A large-scale real-world dataset for transparent object depth completion and a grasping baseline

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 001ac83f-592a-4c96-9fd0-495a371dceb9 · outbound

This paper cites Graspnet-1billion: A large-scale benchmark for general ob- ject grasping.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Graspnet-1billion: A large-scale benchmark for general ob- ject grasping

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 29a0a667-24a6-42f5-a0a6-8d7d636d795e · outbound

This paper cites D-sco: Dual-stream conditional diffusion for monocular hand-held object reconstruction.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation D-sco: Dual-stream conditional diffusion for monocular hand-held object reconstruction

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 7051288f-c59d-4441-b338-44d18ac512a6 · outbound

This paper cites Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 97344fca-977c-403d-8b25-e7745536910f · outbound

This paper cites Addressing nega- tive transfer in diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Addressing nega- tive transfer in diffusion models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ff4ff99a-b66a-4472-9872-3662391459ec · outbound

This paper cites Efficient diffu- sion training via min-snr weighting strategy.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Efficient diffu- sion training via min-snr weighting strategy

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0fe94305-14dd-46a3-af12-4cd0ecbc02c2 · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c8762355-6077-4943-84e2-45dacb49e7ed · outbound

This paper cites Fourier transporter: Bi-equivariant robotic manipulation in 3d.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Fourier transporter: Bi-equivariant robotic manipulation in 3d

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 58a8d01a-8e65-46a2-99f0-13ab9d26d4b0 · outbound

This paper cites Robotic perception of transparent objects: A review.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Robotic perception of transparent objects: A review

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0e032ab6-90e0-447a-90b4-a71e6374f106 · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation af40b46d-aea4-4a99-bf70-6427f278382a · outbound

This paper cites Open3dsg: Open- vocabulary 3d scene graphs from point clouds with queryable objects and open-set relationships.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Open3dsg: Open- vocabulary 3d scene graphs from point clouds with queryable objects and open-set relationships

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e7344adc-2c52-412b-9805-82c087eb9257 · outbound

This paper cites Alleviating exposure bias in diffusion mod- els through sampling with shifted time steps.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Alleviating exposure bias in diffusion mod- els through sampling with shifted time steps

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation de7dbca9-2967-4db9-938e-c383c914ee06 · outbound

This paper cites Fdct: Fast depth completion for transparent objects.IEEE Robotics and Automation Letters, 8(9):1893–1912, 2023.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Fdct: Fast depth completion for transparent objects.IEEE Robotics and Automation Letters, 8(9):1893–1912, 2023

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 16d92551-72d3-4670-99a2-d4e6902dbb02 · outbound

This paper cites On error propa- gation of diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation On error propa- gation of diffusion models

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 76c2dddd-5151-4c15-be77-578bd6b0df2c · outbound

This paper cites Common diffusion noise schedules and sample steps are flawed.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Common diffusion noise schedules and sample steps are flawed

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f0093de9-cd07-4143-a4fd-141188317cdf · outbound

This paper cites Wonder3d: Single image to 3d using cross-domain diffusion.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Wonder3d: Single image to 3d using cross-domain diffusion

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 696b53c9-7bc7-4880-9eec-f2d88e1416ed · outbound

This paper cites Fine-tuning image-conditional diffusion models is easier than you think.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Fine-tuning image-conditional diffusion models is easier than you think

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b68fd948-c271-40d7-9c0f-485df5f12d70 · outbound

This paper cites Elucidating the exposure bias in diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Elucidating the exposure bias in diffusion models

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b57a05d3-aa33-4e5e-a6cf-e265442e4722 · outbound

This paper cites Discovering clone negatives via adaptive contrastive learning for image-text matching.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Discovering clone negatives via adaptive contrastive learning for image-text matching

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 56af90e0-cdba-4a2b-b795-48717866ea7c · outbound

This paper cites Switch diffusion trans- former: Synergizing denoising tasks with sparse mixture-of- experts.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Switch diffusion trans- former: Synergizing denoising tasks with sparse mixture-of- experts

Reference 24

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d4320967-7bad-4326-beba-789f7d2f6fc8 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation High-resolution image syn- thesis with latent diffusion models

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 743016a1-bcb9-4f17-b3bf-cd0bc1cf575f · outbound

This paper cites Clear grasp: 3d shape estimation of transparent objects for manip- ulation.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Clear grasp: 3d shape estimation of transparent objects for manip- ulation

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 30d9a761-6417-4dad-9fe3-498be7d10d24 · outbound

This paper cites Progressive distillation for fast sampling of diffusion models.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Progressive distillation for fast sampling of diffusion models

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 03843762-c380-4a4b-b3b7-4f23017dbcd3 · outbound

This paper cites Mor- pheus: Neural dynamic 360deg surface reconstruction from monocular rgb-d video.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Mor- pheus: Neural dynamic 360deg surface reconstruction from monocular rgb-d video

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:27.912904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:24.805697Z digest=sha256:f88a411d6189e0c55bed3708d9b1613f97540720fd9cff5be802f4199f40615f

Observation b48f7732-5598-4c34-a96a-7c2809415af8 · outbound

This paper cites Gˆ3-lq: Marrying hyperbolic alignment with explicit semantic-geometric mod- eling for 3d visual grounding.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Gˆ3-lq: Marrying hyperbolic alignment with explicit semantic-geometric mod- eling for 3d visual grounding

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:27.716723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:24.867651Z digest=sha256:adbd95849c99d9f14553c5e66d9fe1202b253ea98f5875871387f3ec7d03b2c8

Observation 9ad555b0-c5ff-404a-848a-7287202ca485 · outbound

This paper cites D3roma: Disparity diffusion-based depth sensing for material-agnostic robotic manipulation.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation D3roma: Disparity diffusion-based depth sensing for material-agnostic robotic manipulation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:27.500535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:24.961828Z digest=sha256:9ab5f4e0dd12818345ae981804b78955bab150286dd45d9c3cb30f5572edd139

Observation eea45d2b-56ef-4a91-9828-3500c4cf2f8d · outbound

This paper cites Layeredflow: A real-world benchmark for non-lambertian multi-layer optical flow.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Layeredflow: A real-world benchmark for non-lambertian multi-layer optical flow

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:27.320293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.030716Z digest=sha256:f0efb80630bc821e85ccdb528841eed52b60dcb17b8dbfc4ed3b0e85e8c9302a

Observation bbb9ea6b-e459-4784-ad76-e7de292c8bee · outbound

This paper cites Unsupervised modality adapta- tion with text-to-image diffusion models for semantic seg- mentation.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Unsupervised modality adapta- tion with text-to-image diffusion models for semantic seg- mentation

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:27.136541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.116062Z digest=sha256:a4d30a04b8bc6ce71f4319fd174bcead349929c797441c57d5e132ecf08c409c

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

This paper cites What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?.

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.

source=pdf_text observed=2026-08-06T22:41:25.195006Z digest=sha256:c68087198c9d18399323ff11748cf69ac73d2d7cfc9351856bf34b6703643a90

Observation b91fd710-781a-4c39-b29f-e8e6745a9365 · outbound

This paper cites Seeing glass: Joint point-cloud and depth completion for transparent objects.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Seeing glass: Joint point-cloud and depth completion for transparent objects

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.961465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.279949Z digest=sha256:303a9a2bedd79e49864ee054e8be333d1d668955faa96640250b90e651d409fd

Observation 863bb207-41c2-47b0-8735-113c7bbb3c24 · outbound

This paper cites 3d diffusion policy: Gen- eralizable visuomotor policy learning via simple 3d repre- sentations.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation 3d diffusion policy: Gen- eralizable visuomotor policy learning via simple 3d repre- sentations

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.786569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.359769Z digest=sha256:a847c67bac01022bfc7ddba59c41e793aae84f5a7198f5bea4b098aabc2fc1fc

Observation d2d9924f-c9de-4cc1-ac14-f49d289af5e3 · outbound

This paper cites Tcrnet: Transparent object depth completion with cascade refinements.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Tcrnet: Transparent object depth completion with cascade refinements

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.624491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.430529Z digest=sha256:42e5a938de03bf944c33bf30ea716a4266089fe6db40ff5c40632b66d4c32323

Observation 660a434e-1227-4012-83b1-e55b77abae77 · outbound

This paper cites Omni6dpose: A benchmark and model for universal 6d object pose estima- tion and tracking.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Omni6dpose: A benchmark and model for universal 6d object pose estima- tion and tracking

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.454594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.512915Z digest=sha256:08f3f9ab9d2039056cb8bc5cf3ef465665f7b5decc2c819afac08731890d08c1

Observation 13443693-28f2-4f68-b428-65c1ad34aa09 · outbound

This paper cites Beta-tuned timestep diffusion model.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Beta-tuned timestep diffusion model

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.292160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.623111Z digest=sha256:37013b0f00be33a9be9b881fe4aeed2dc0498c6b491309623a714c0d28061a96

Observation 3d7df933-b6c6-4b51-985e-76938df4ee44 · outbound

This paper cites Point cloud matters: Rethinking the impact of different observation spaces on robot learning.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Point cloud matters: Rethinking the impact of different observation spaces on robot learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.137377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.713360Z digest=sha256:1df8f5fd678449a83790a9feb94808311cc10e1271845c17d76f5cb630ac02de

Observation 63ee3990-3e47-4807-99f0-76ad8885c0d7 · outbound

This paper cites Rgb-d local implicit function for depth completion of transparent objects.

DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation Rgb-d local implicit function for depth completion of transparent objects

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:41:26.004984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:41:25.797696Z digest=sha256:d4b813f388ab8bc67968c7bed461309eefee96be552999c3856dbdd31caee082

Pith citing papers

No inbound Pith citation observations are available.