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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 8 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 2026-08-08T06:32:00.761636+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
raw_fallback, observed 2026-08-07T12:24:01.114223Z

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.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.216685Z digest=sha256:f9a92ba073aa17d0286bbb91c5357e7cad4572d77a527d2de04b28083a013dfb

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

Resolution
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:f7241b3c26da432dea3d519dfc3792055478b064925f27476c26d672c770fd2b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.384342Z digest=sha256:bbd06960a03e73be30c570bd8faccc47101cf45865900cb05cf79387a9673cf3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.494842Z digest=sha256:2d2d551fe33237f39e8989c08f1a24df80df50f840e05ac680d94195b3e267a1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.604902Z digest=sha256:30e7aa1d5b4d8c2b0dda77adec5a0d7cc227f78daafba6de420157c346dae47b

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=sha256:94054f6ad2886950608b7e5b312fd37d756c7c42e77885111e7e96c818c60a72

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.814785Z digest=sha256:789bc3dd76d2771e589b679446cf98e21a7bf878f6f5742b67670ee081e79e21

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:53.899508Z digest=sha256:549210a6c3c7f68e6ee1e1e2ba6797015faec277e6d733599adebdc220cfd2e1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.005433Z digest=sha256:023b00e8a95e30e7372ddaa8fe6bcaff91fd2eee97b97a49ce621f924213058b

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=sha256:55974a927c44a8731fb9d846cf3cc53d2333bb6e534227bfd5e256ee3c1b2ea2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.159741Z digest=sha256:5536cdf84bf9dd6a41f1b655ab5cf7a05d2594ed47df1b5834c4a4d14624f7a9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.276664Z digest=sha256:25fbe92b5229c4931c7ab478d89d3c81e97cd5dac0b75f4b7988172e20f1a446

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.351624Z digest=sha256:8067b18edaef2c62e160b722f5bdc01e3e9d54bfeb80e61ca1dafb86ec3ea79c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.439360Z digest=sha256:7140423eed2aabdef960b3ea060becdcc1a1ad68b8b71733d8f0fac2d6d60fd2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.526582Z digest=sha256:1026c319a58dba9f3d11be7d94447ec459e5cd55e59c91dee01561ff398d9945

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.622873Z digest=sha256:64ebf4609e35dca6be4d7fb17b080405512d9342fdec7ab874659a1358937409

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:54.742072Z digest=sha256:e21439a4491d7f61ead0ac4cc712c687ae6ca67a720bf798270d76b0a5f927a0

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=sha256:4c1dcaadd2b23c59174d292fead91ffa0e606b1efac615c91ece94e381d4f5e7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.018762Z digest=sha256:7dc1a044ca96df63ee0189a27a9f8cff4d1fd8c77d36097813c413714cc3cd88

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:da184ef16d7a233fbbe8302c51d266d867ba708132b9e88d213c9ccdb2bf4550

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.197784Z digest=sha256:9e45610dd3e0174c6dc30e7409404c85515b4d2255ec9912e3529fb44ecc0cdc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.359902Z digest=sha256:bf4eee386c54bcd7a1b18cbca3f9bdc8ac3534bdd36dec061ef62c25d9d95704

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.494310Z digest=sha256:e972e932f112f068d4f81dc2ef0db402d314b568c4d971e75d2b89e2b0ecc6d8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.585110Z digest=sha256:417f65806c98b97df57bdf36ed6d791820ab2173400a6c629c0ea2e5a928dadf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.698967Z digest=sha256:9d0b86754482e0ce358fb69c4fe82364dc2f94e949c2c66f174250a657f004cd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.836702Z digest=sha256:bde1c73770e3298114e17dd1a5dfdcf42a1080b35334fea10c084d2a5275473a

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=sha256:8079df877cad2e029384143a0e73cbef608f4e2fa950222fe6d45bdfb56e07d1

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=sha256:702e4bded87a42dc635ba76d416cb607f85e0f80f626db39ff333855774db7da

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=sha256:130fb51a640774b5033dca35a432df1eca80c2cb6b3cc906c52cd61fde03d816

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:cc498fcfe43b055e607ca74ff6de376fa5beb65d0a3f9500f362bba819dfe7bd

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=sha256:01e8be5ad1068847b16f4756cc3f5553e07ca751038596b5eb6bbedf1e9e4156

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:56.742378Z digest=sha256:770db969a6905720185987ba13d1a67a3275e53042fb9639907841ac2014ebfd

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=sha256:8970dd140ebaf883deedaed68de5877e383a6952dceb9b8635dc47d200abae56

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:56.890619Z digest=sha256:4c5543871361384d737ce284594b8ce19d68463eda7ed94ef0a19fe838463f19

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:56.981133Z digest=sha256:b68aa440b3cfeb25ec05acf6896f68714d091f43f7f5624897c5cf21dbf2c70c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:57.045610Z digest=sha256:054bbf0136255d707226af2e8b3aedd1a59d47f54fb992d9dcb2e960e845cca1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:23:55.948705Z digest=sha256:9e413785ebbe14e7a521ceda5a2b310c096a64c2e7b555e340bad410e6343bae

Pith citing papers

No inbound Pith citation observations are available.