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Paper Citation Record · LEDGER

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.24636.

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

pith.paper-citation-record.v1
2505.24636 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:23:57.045610Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy26
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3fd44ac7-e594-4884-b877-8841682d90da · outbound

This paper cites Selective harvesting robotics: current research, trends, and future directions,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Selective harvesting robotics: current research, trends, and future directions,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1c78ed41-11c7-44bb-821f-34f20d5d1d97 · outbound

This paper cites Algorithm design and integration for a robotic apple harvesting system,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Algorithm design and integration for a robotic apple harvesting system,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.967776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.216685Z digest=sha256:4dccd3705153f8a56d15df4f3950abf3f2921caacda2cc274f3e21b7b60c788c

Observation f0e7291f-ff4c-4077-aa58-2dc6b42d76aa · outbound

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

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare

Reference 3

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unresolved
no resolver link, observed 2026-08-07T12:23:53.291725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:53.291725Z digest=sha256:65d1fdf3070664e84a3e53119859b1515ae7a274f53f96cc202a1200debf13c2

Observation 787ed39c-c2cf-4a08-b782-744896f40a7b · outbound

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

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data FoundationPose: Unified 6d pose estimation and tracking of novel objects,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.795797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.384342Z digest=sha256:5f05821097e0154091440a12e9a394718e3e9850ff971b9a83098adbe8299dcf

Observation 3cd5a5df-661b-47d1-b537-739116d439c6 · outbound

This paper cites Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.652916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.494842Z digest=sha256:bfcaa6ff60051ed426c57fe14d40ce412b736261cba2c093d9b898d23d20240e

Observation 42064ac0-e47b-43a1-bac2-b2e2a4833429 · outbound

This paper cites Cosypose: Consistent multi-view multi-object 6d pose estimation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Cosypose: Consistent multi-view multi-object 6d pose estimation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.513277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.604902Z digest=sha256:0f9c5f907b5f5aad97492dab88df2e4bd358159850063ada6e3896f6c4a20bbe

Observation ca32af38-a079-49cb-8607-6acda5c80922 · outbound

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

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Gigapose: Fast and robust novel object pose estimation via one correspondence,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:53.744405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:53.744405Z digest=sha256:d71e49c4e2e481cd3409d13b25100b03ef6380790507dd4c8624916b8a35c1ea

Observation f5b4f081-7757-410c-8a4f-0877625fd7b3 · outbound

This paper cites Normalized object coordinate space for category-level 6d object pose and size estimation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Normalized object coordinate space for category-level 6d object pose and size estimation,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.381158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.814785Z digest=sha256:9804cfc622cd51a161459ca5cc98324d01a9766de00c9cf2a2a93fa037ad919b

Observation 2ad6c734-3288-4efc-9fca-da678ba89dde · outbound

This paper cites SOCS: Semantically-aware Object Co- ordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations ,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data SOCS: Semantically-aware Object Co- ordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations ,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.251626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:53.899508Z digest=sha256:f57684f47390cf9a50e4b8922e6a4a063edd130b4bb1a6bd1c2b742b54887003

Observation 3fcb1073-770b-47e3-8b38-d4b8379e438d · outbound

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

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data BOP: Benchmark for 6D object pose estimation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:00.122540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.005433Z digest=sha256:0eaed7adc3b99c7eaaf054e972ccf8ef588024dca5dd86c6223a9b005efd8495

Observation 137365fa-d8aa-4f29-bdc0-498cd4c8b92b · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data ShapeNet: An Information-Rich 3D Model Repository

Reference 11

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unresolved
no resolver link, observed 2026-08-07T12:23:54.089156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:54.089156Z digest=sha256:b8f10caaa2b6abc81ee7ad4c740930439c466770a90fc011aa9f07f16927adaf

Observation 977e6b87-fe96-47ed-97d4-9b1b34edd066 · outbound

This paper cites Google scanned objects: A high-quality dataset of 3d scanned household items,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Google scanned objects: A high-quality dataset of 3d scanned household items,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.997160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.159741Z digest=sha256:12a25167dc57d042ee8d3574ee4c02b8945a817705f007a69b106ae461e6acae

Observation a6094dc4-d24c-43f3-aebd-e9afe874295c · outbound

This paper cites Objaverse: A universe of annotated 3d objects,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Objaverse: A universe of annotated 3d objects,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.854520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.276664Z digest=sha256:877ca42d15ce065abe6654b9c37fc967011ec1d71344c323947370e9d95e60ac

Observation ff133740-7f30-481f-a3b9-cc0ad4487599 · outbound

This paper cites Catgrasp: Learning category-level task-relevant grasping in clutter from simulation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Catgrasp: Learning category-level task-relevant grasping in clutter from simulation,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.685765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.351624Z digest=sha256:c2c1a431fb36f4b53604b5b6cfb133a301027ca56a07c109faed6b949ddce9a3

Observation 98985151-9c32-492c-9870-7799eba8405a · outbound

This paper cites Shape prior deformation for categorical 6d object pose and size estimation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Shape prior deformation for categorical 6d object pose and size estimation,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.544879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.439360Z digest=sha256:1795c4f7586a04802aed9c5bdc550e8520c99ad10479400afa6a5a529ba78798

Observation 217fb835-47f5-4a9c-995c-bd6d6c95057d · outbound

This paper cites Ssp- pose: Symmetry-aware shape prior deformation for direct category- level object pose estimation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Ssp- pose: Symmetry-aware shape prior deformation for direct category- level object pose estimation,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.400054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.526582Z digest=sha256:2642e97f59450d42d986dc6772bd203a30b3f569d04db565f8eda85bd69f3c46

Observation 65113e31-d328-4a1f-bcdf-8b4fa82525cc · outbound

This paper cites Shapo: Implicit representations for multi-object shape appearance and pose optimization,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Shapo: Implicit representations for multi-object shape appearance and pose optimization,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.248504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.622873Z digest=sha256:75d02482b223a09276fb9fa5da769f24bd28fc57baea4a79f4f812f0b6aaa605

Observation df2f0042-133b-4904-8d71-23bd41ddde4d · outbound

This paper cites Disp6d: Disentangled implicit shape and pose learning for scalable 6d pose estimation,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Disp6d: Disentangled implicit shape and pose learning for scalable 6d pose estimation,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:59.075182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:54.742072Z digest=sha256:44fb4198f5cf859733d7682f3e5199f6ce2907f854cd4b2439b107c67dfc9c64

Observation e072a866-95a9-456e-b52b-b991fcd46457 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:54.863514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:54.863514Z digest=sha256:27ad4ee26a550fa21a134622c9a0f575451b7b62fa55717fd93e26dc113fb2e6

Observation f770a009-d2d9-46db-bf33-797f6c29f3b4 · outbound

This paper cites NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:23:57.214177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.018762Z digest=sha256:0ebb8ca47578b201ac8207b51c5d7abbdab6681cede16fb50c279d599ec81a59

Observation 9d408460-856a-42dd-8a6d-6b6071e4ef04 · outbound

This paper cites Blenderproc2: A procedural pipeline for photorealistic rendering,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Blenderproc2: A procedural pipeline for photorealistic rendering,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:55.142724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:55.142724Z digest=sha256:d2ca3f300b08349b6a666ebe855d86beac079539dec66deffc808a789d7d6909

Observation 83dcc5e1-d6a1-4be8-96e8-e507de035700 · outbound

This paper cites A realistic synthetic mushroom scenes dataset,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data A realistic synthetic mushroom scenes dataset,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.916378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.197784Z digest=sha256:3779d935b1134e28921aa3f808790a46df5d6e56f9f46aa35dc008d28772d7a8

Observation cba94e19-6cb7-4898-b26d-3ca683c57917 · outbound

This paper cites Mushroom segmentation and 3d pose estimation from point clouds using fully convolutional geometric features and implicit pose encoding,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Mushroom segmentation and 3d pose estimation from point clouds using fully convolutional geometric features and implicit pose encoding,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.789434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.359902Z digest=sha256:0803f171963f06231d385bff1ab40757c96d9a8a3058d353784913943d51b086

Observation 355519be-a792-4058-8503-8f37562722fe · outbound

This paper cites Tomato harvesting robotic system based on deep-tomatos: Deep learning network using transformation loss for 6d pose estimation of maturity classified tomatoes with side-stem,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Tomato harvesting robotic system based on deep-tomatos: Deep learning network using transformation loss for 6d pose estimation of maturity classified tomatoes with side-stem,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.647174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.494310Z digest=sha256:fb4396ebbbc7d86b6f99f242d73e6e2370aa6bf4cf0a800f1fa5fe2bc824418b

Observation 1460786f-2fb9-4806-9fe4-2df84f361246 · outbound

This paper cites Single-shot 6dof pose and 3d size estimation for robotic strawberry harvesting,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Single-shot 6dof pose and 3d size estimation for robotic strawberry harvesting,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.501424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.585110Z digest=sha256:cb82ef70ae19115e6d1ba4cdc13d4c4a19cbba40af27c604152416db233d8d01

Observation 4090aeac-4db4-4e4d-9cb2-cdc084667239 · outbound

This paper cites Enhanced 6d pose estimation for robotic fruit picking,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Enhanced 6d pose estimation for robotic fruit picking,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.371063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.698967Z digest=sha256:fd5dc236e9a1317ef270cc75aff467cd5a6e81ab06152ba8ce86ce659cf23a0e

Observation baac30e0-0daf-40bd-a256-e345663e6908 · outbound

This paper cites Experimental comparison of two 6d pose estimation algorithms in robotic fruit-picking tasks,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Experimental comparison of two 6d pose estimation algorithms in robotic fruit-picking tasks,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.207443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.836702Z digest=sha256:6a87cc04a53b240997bbe0a840a63cd3a7dd2d1af62fa20f9b1b3911959a3898

Observation 4b499ea8-4e75-4065-8e40-a3ed9820aaaa · outbound

This paper cites an unresolved cited work.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.041108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.041108Z digest=sha256:d0c74dc05f9b01f4bc290e327d083f6a9198959be62b2f2e42754c1eb68a873f

Observation 275eec7b-758e-4e4a-b492-1193c737ebac · outbound

This paper cites Least-squares estimation of transformation parameters between two point patterns,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Least-squares estimation of transformation parameters between two point patterns,

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.160134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.160134Z digest=sha256:07d2cf9c958c5da54b438f074dbec6dc87cf8a5952aca1a59a9bc2567c219e1b

Observation d674de13-69af-4105-8355-f7a5cfd322ff · outbound

This paper cites Adding conditional control to text-to-image diffusion models,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Adding conditional control to text-to-image diffusion models,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.324783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.324783Z digest=sha256:2fef0b3c96b5599d6aeee3999293ff9a1fc39f3134b8ae52ce519518a31bd597

Observation 82c967e8-8053-4cb1-80f2-cd247a52020e · outbound

This paper cites Ultralytics yolo11,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Ultralytics yolo11,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.453906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.453906Z digest=sha256:0e673d6f35ef118a6b030f25dbd7bde57e247641751340dc1ee910181ab5affb

Observation 5d9d290a-3f22-4e62-a9e1-7972b87df94a · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.621199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.621199Z digest=sha256:d202e83ea85ebc317e3dc194d19142f00412b07a54bab35a3e3452ee54cc9ba8

Observation 2c5bad36-a071-46bf-bc16-1da3e510e049 · outbound

This paper cites Single image 3d object detection and pose estimation for grasping,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Single image 3d object detection and pose estimation for grasping,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:57.869636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:56.742378Z digest=sha256:1802e86c426732ca9d749bfa86328ef59ad3adf0a635bd427f2e619f94edf0cc

Observation bba376b5-fefb-4b13-bfa6-c2b5affdc0b7 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Adam: A Method for Stochastic Optimization

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:56.809847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:56.809847Z digest=sha256:0c4666240703df70ac46bdc29c29cc32514bb69bfc61f88488c9d9198812bc57

Observation 5114e63e-9151-495f-892e-759c68e88fce · outbound

This paper cites epnp: An accurate o(n) solution to the pnp problem,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data epnp: An accurate o(n) solution to the pnp problem,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:57.727102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:56.890619Z digest=sha256:96891e7b7ef9262f4d09be7a0f8b1c819edcd16203d9d4279bd4338d992c9de6

Observation 4c67b0d2-1f15-4354-b26f-4b2e7fac3672 · outbound

This paper cites Gpv-pose: Category-level object pose estimation via geometry-guided point-wise voting,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Gpv-pose: Category-level object pose estimation via geometry-guided point-wise voting,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:57.534944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:56.981133Z digest=sha256:387b6dd7c99fb9737ec20a5f81ab45f6efba1904d47ac8b074a35b79b97a7b77

Observation 3e04bba6-a3c8-4aa3-8d97-5b6c5f5bbd9d · outbound

This paper cites Dualposenet: Category- level 6d object pose and size estimation using dual pose network with refined learning of pose consistency,.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Dualposenet: Category- level 6d object pose and size estimation using dual pose network with refined learning of pose consistency,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:57.384456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:57.045610Z digest=sha256:8c4216fa703978301db7ac128cc0989759556c54d11563a24294568f9d2b4b4d

Observation f8245154-fda1-490e-949e-6e9cfa7a8e2d · outbound

This paper cites Available: https://www.mdpi.com/2218-6581/13/9/127.

Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data Available: https://www.mdpi.com/2218-6581/13/9/127

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:23:58.069440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:23:55.948705Z digest=sha256:bcdf41ff6dbe439c1d709a817b25abd332a946ec11f619cb7c6fd3c79c7cac7e

Pith citing papers

No inbound Pith citation observations are available.