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Paper Citation Record · LEDGER

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes

As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.23669.

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

pith.paper-citation-record.v1
2607.23669 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T16:22:12.997447Z

measured 36 of 36 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.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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  • verified fuzzy0
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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Outbound references

Observation 57112e7b-5ccb-4f76-9956-e3323d2f3b02 · outbound

This paper cites A practical robotic grasping method by using 6-D pose estimation with protective correction,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes A practical robotic grasping method by using 6-D pose estimation with protective correction,

Reference 1

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Observation f3d4f040-4b38-47af-98a6-dfd640f0f938 · outbound

This paper cites Real- time markerless tracking for augmented reality: The virtual visual servoing framework,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Real- time markerless tracking for augmented reality: The virtual visual servoing framework,

Reference 2

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Observation 8a63e6fe-4f05-4c60-9ee8-4f2256ca87df · outbound

This paper cites Socially conscious navigation of mobile robots based on deep reinforcement learning,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Socially conscious navigation of mobile robots based on deep reinforcement learning,

Reference 3

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Observation 2c61cb9c-be97-4203-85aa-605d1109dbd6 · outbound

This paper cites Deep learning-based object pose estimation: A comprehensive survey,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Deep learning-based object pose estimation: A comprehensive survey,

Reference 4

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Observation 328187ed-0a48-4d9d-9d19-8c28860486a4 · outbound

This paper cites FoundationPose: Unified 6D pose estimation and tracking of novel objects,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes FoundationPose: Unified 6D pose estimation and tracking of novel objects,

Reference 5

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source=pdf_text observed=2026-07-30T16:22:10.348622Z digest=sha256:632fa8c1d27bce0c6d3558bb64620505235bb9d423e3f1db3652ee837fc540ba

Observation 5b285d22-e6a8-474e-af26-2c02015aa48a · outbound

This paper cites GigaPose: Fast and robust novel object pose estimation via one correspondence,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes GigaPose: Fast and robust novel object pose estimation via one correspondence,

Reference 6

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Observation 1f6e31e3-6ca7-49d0-8b11-6c34b7d43195 · outbound

This paper cites Dynamicpose: Real-time and robust 6d object pose tracking for fast-moving cameras and objects,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Dynamicpose: Real-time and robust 6d object pose tracking for fast-moving cameras and objects,

Reference 8

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Observation 842dcc58-cbe3-40de-9b67-f89f6d91a244 · outbound

This paper cites BOP: Benchmark for 6D object pose estimation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes BOP: Benchmark for 6D object pose estimation,

Reference 9

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Observation 8b37a18b-9f2c-4bef-9e44-888611899133 · outbound

This paper cites Category-level 6-D ob- ject pose estimation with learnable prior embeddings for robotic grasping,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Category-level 6-D ob- ject pose estimation with learnable prior embeddings for robotic grasping,

Reference 10

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Observation 93a33d08-8866-41f1-98e5-1d77c96861ec · outbound

This paper cites Zephyr: Zero-shot pose hypothesis rating,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Zephyr: Zero-shot pose hypothesis rating,

Reference 11

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Observation 8dd70d86-b15c-44f5-a2e5-efb6fe684c28 · outbound

This paper cites OVE6D: Object viewpoint en- coding for depth-based 6D object pose estimation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes OVE6D: Object viewpoint en- coding for depth-based 6D object pose estimation,

Reference 12

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source=pdf_text observed=2026-07-30T16:22:10.971504Z digest=sha256:cf6f2b9f4588cb6e3ec095800664ce102b4c772779b9c7947464137a01f0cbd1

Observation 9e989ee5-76ca-4bea-844e-b8783a06894a · outbound

This paper cites MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare,

Reference 13

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Observation 323e8c95-41ed-44d6-b71a-6a073cb98d71 · outbound

This paper cites Genflow: Generalizable recurrent flow for 6d pose refinement of novel objects,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Genflow: Generalizable recurrent flow for 6d pose refinement of novel objects,

Reference 14

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source=pdf_text observed=2026-07-30T16:22:11.164818Z digest=sha256:0c7bc521fb036ba6aa0c7ddaba5ac17ab701cfce5926a0405684ffdb0fc78b72

Observation 0a267b7a-5e2f-4ce9-9331-22d96164ac24 · outbound

This paper cites Sam-6d: Segment anything model meets zero-shot 6d object pose estimation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Sam-6d: Segment anything model meets zero-shot 6d object pose estimation,

Reference 15

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Observation 554a256a-5f28-456e-8c7f-0d41e54c28e9 · outbound

This paper cites Keypoint- guided efficient pose estimation and domain adaptation for mi- cro aerial vehicles,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Keypoint- guided efficient pose estimation and domain adaptation for mi- cro aerial vehicles,

Reference 16

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Observation 83b4357f-3996-4331-af78-ca8d0988b9cf · outbound

This paper cites ZS6D: Zero-shot 6D object pose estimation using vision transformers,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes ZS6D: Zero-shot 6D object pose estimation using vision transformers,

Reference 17

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Observation 66afc5e8-d7bc-4df2-a364-8a19f600e18d · outbound

This paper cites Foundpose: Unseen object pose estimation with foundation features,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Foundpose: Unseen object pose estimation with foundation features,

Reference 18

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Observation bef93549-5a8e-4534-88bf-f98a28fee11c · outbound

This paper cites Cnos: A strong baseline for cad-based novel object segmentation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Cnos: A strong baseline for cad-based novel object segmentation,

Reference 19

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Observation a82c3a26-5c36-43c1-a5e3-9d6840d390c9 · outbound

This paper cites Segment Anything.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Segment Anything

Reference 20

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Observation ef94144c-0dd7-49f0-b48b-f372f944ca6f · outbound

This paper cites Freeze: Training- free zero-shot 6d pose estimation with geometric and vision foundation models,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Freeze: Training- free zero-shot 6d pose estimation with geometric and vision foundation models,

Reference 21

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Observation 1acca0a2-62c5-4b78-9b5a-6171c28e969f · outbound

This paper cites Learning general and distinctive 3D local deep descriptors for point cloud registration,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Learning general and distinctive 3D local deep descriptors for point cloud registration,

Reference 22

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Observation 1b61e7ed-a0c0-4cf7-9f2d-0c5ae5b5732b · outbound

This paper cites Object pose estimation via the aggregation of diffusion features,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Object pose estimation via the aggregation of diffusion features,

Reference 23

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Observation bb903985-9c21-4efd-85eb-276479c251d4 · outbound

This paper cites Diffusion Features for Zero-Shot 6DoF Object Pose Estimation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Diffusion Features for Zero-Shot 6DoF Object Pose Estimation,

Reference 24

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Observation 60fe7384-e05d-41de-bcac-50d36a624b41 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes DINOv2: Learning Robust Visual Features without Supervision

Reference 25

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Observation 5b3baafd-7c72-44da-be1c-fb70c99aebda · outbound

This paper cites Ai flow: Perspectives, scenarios, and approaches,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Ai flow: Perspectives, scenarios, and approaches,

Reference 26

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correction dated 2026-06-03. Source: crossref record 10.1007/s44336-026-00039-y->10.1007/s44336-025-00031-y:correction, observed 2026-07-11T02:57:14.312584+00:00. This notice travels one citation hop only.

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Observation 29efb459-74b5-4aa0-866e-b9242e60a717 · outbound

This paper cites Ai flow at the network edge,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Ai flow at the network edge,

Reference 27

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Observation 163c935f-f625-4ea2-9da7-963c79e7969e · outbound

This paper cites Generative Transmission: Rethinking Computation, Bandwidth, and Memory in Communication.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Generative Transmission: Rethinking Computation, Bandwidth, and Memory in Communication

Reference 28

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Observation e98d0a2a-d0ca-49ef-b490-8b662f37baa1 · outbound

This paper cites Optical image processing and applications empowered by vision-language models,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Optical image processing and applications empowered by vision-language models,

Reference 29

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Observation b5852ce2-4095-4941-9571-1f92331e981b · outbound

This paper cites DeepIM: Deep iterative matching for 6D pose estimation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes DeepIM: Deep iterative matching for 6D pose estimation,

Reference 30

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Observation 151591be-a638-4d8e-b843-516aeb9d567b · outbound

This paper cites Poserbpf: A rao-blackwellized particle filter for 6d ob- ject pose tracking,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Poserbpf: A rao-blackwellized particle filter for 6d ob- ject pose tracking,

Reference 31

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Observation 5729eb81-eceb-407c-ad62-09be23d2f99e · outbound

This paper cites Iterative corresponding geometry: Fusing region and depth for highly efficient 3D tracking of textureless objects,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Iterative corresponding geometry: Fusing region and depth for highly efficient 3D tracking of textureless objects,

Reference 32

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Observation 0725fa57-ec22-4ea7-8e7b-9a43e865bcc3 · outbound

This paper cites BundleTrack: 6D pose tracking for novel objects without instance or category-level 3D models,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes BundleTrack: 6D pose tracking for novel objects without instance or category-level 3D models,

Reference 33

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Observation 5f8c1046-2f27-42ed-9abe-275d29c5549e · outbound

This paper cites Putting the Object Back into Video Object Segmentation,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Putting the Object Back into Video Object Segmentation,

Reference 34

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Observation f0229f80-4ce6-44e1-97ae-4a9f937fa220 · outbound

This paper cites PoseCNN: A Con- volutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes PoseCNN: A Con- volutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes,

Reference 35

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Observation 608d09b0-c737-411e-9264-182102459bc2 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes SAM 2: Segment Anything in Images and Videos

Reference 36

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Observation 92e3675a-753d-4c03-9573-82377c895af8 · outbound

This paper cites Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework,.

RRTrack: Robust and Recoverable Object 6D Pose Tracking for Dynamic Scenes Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework,

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.