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Paper Citation Record · LEDGER

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning

As of 11 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.14820.

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

pith.paper-citation-record.v1
2507.14820 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:51:27.979467Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

46 of 46 outbound references displayed

  • verified exact1
  • verified fuzzy39
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7182a003-8c82-48ce-a852-72abcd041d50 · outbound

This paper cites Sg-bot: Object rearrangement via coarse-to-fine robotic imagination on scene graphs,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Sg-bot: Object rearrangement via coarse-to-fine robotic imagination on scene graphs,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.855654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 990a31fe-c412-4dfc-b5ea-1b312dc3056c · outbound

This paper cites Structformer: Learning spatial structure for language-guided semantic rearrangement of novel objects,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Structformer: Learning spatial structure for language-guided semantic rearrangement of novel objects,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.835336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:24.381811Z digest=sha256:f60285e619aa2a948d50352802d0a8fe9d3237e3039f0ea328316cf33e6c4444

Observation 6f3f2f10-7bb1-4054-a218-9a592cc5320d · outbound

This paper cites Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.816664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:24.446676Z digest=sha256:7718f5c29386c7f066eadcfd768337e5547e532dde536d7bbf8c77b11fbd2106

Observation b0b319ca-e121-4698-91b7-70012b3e503c · outbound

This paper cites Language embedded radiance fields for zero-shot task-oriented grasping,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Language embedded radiance fields for zero-shot task-oriented grasping,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.797106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:24.547714Z digest=sha256:e0b63c1c8280350e5d2ebc691b1f98a9daa20a60dbf87c6500068c4bb397ac5d

Observation f23192fc-5af7-4519-a1dd-ff47f833e230 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Pointnet: Deep learning on point sets for 3d classification and segmentation,

Reference 5

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unresolved
no resolver link, observed 2026-08-06T15:51:24.678193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:24.678193Z digest=sha256:3bd47b169ee2ae3e05ec4e0500aded208bf6b0ab1ad96a79eedb21c1176f9f8f

Observation 750f55a2-48e3-4ecd-97b2-5ed185920af5 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 6

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unresolved
no resolver link, observed 2026-08-06T15:51:24.746360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:24.746360Z digest=sha256:1c1e9b1dc34ac8936c79cdb07c22ffba7d75ce1d88af3d51c3b81b347f5a3566

Observation b67a1f79-8849-4408-be63-12efac7442bf · outbound

This paper cites Towards scale balanced 6-dof grasp detection in cluttered scenes,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Towards scale balanced 6-dof grasp detection in cluttered scenes,

Reference 7

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raw_fallback, observed 2026-08-06T15:51:33.756679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:24.845539Z digest=sha256:438363432bb2a36c98f9ac9b5611cc03273d2d2b52c024b2ad5c8527b85a36a8

Observation f30ebdde-53bb-4687-932a-d839fcb57ef6 · outbound

This paper cites Rgb matters: Learning 7-dof grasp poses on monocular rgbd images,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Rgb matters: Learning 7-dof grasp poses on monocular rgbd images,

Reference 8

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raw_fallback, observed 2026-08-06T15:51:33.739902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:24.978578Z digest=sha256:159b6189dbcba103e2452f799e28237df1de0e6f0dd47afab8ed96bb47eadae5

Observation 1821fb7d-2205-4642-8591-43b4ad607d4f · outbound

This paper cites Monograspnet: 6-dof grasping with a single rgb image,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Monograspnet: 6-dof grasping with a single rgb image,

Reference 9

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raw_fallback, observed 2026-08-06T15:51:33.680130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.078068Z digest=sha256:8da1af847213f3d91150a0e8ce700875282f1655d4dc44ce4cf11c3342f48176

Observation e67adc7c-e3c0-4890-8822-1e289c30fdba · outbound

This paper cites Keypoint-graspnet: Keypoint- based 6-dof grasp generation from the monocular rgb-d input,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Keypoint-graspnet: Keypoint- based 6-dof grasp generation from the monocular rgb-d input,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.510053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.167061Z digest=sha256:4872bc825ee114bf63e61830a9a23629f54a2f5272487bb309f76703e2caf6ca

Observation 3f1e3505-2abf-4e19-ad81-8e9dfc1a8c2b · outbound

This paper cites Kgnv2: Separating scale and pose prediction for keypoint-based 6-dof grasp synthesis on rgb-d input,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Kgnv2: Separating scale and pose prediction for keypoint-based 6-dof grasp synthesis on rgb-d input,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.370021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.242602Z digest=sha256:3ca32fbd5341658c32a8c578a6c1509531c6471b2e5f4d12f0568de65a9fb23c

Observation 1d2e3b64-6303-4776-b10b-d5826a8c3785 · outbound

This paper cites Gknet: Grasp keypoint network for grasp candidates detection,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Gknet: Grasp keypoint network for grasp candidates detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:33.136863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.309033Z digest=sha256:e8ec06fd41d39b67d637cffe77d2422c60d947b5ba772f3dc163362b3c5aa0af

Observation bfce7494-d20e-41c1-97f8-a1a9fe307d2e · outbound

This paper cites Glace: Global local accelerated coordinate encoding,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Glace: Global local accelerated coordinate encoding,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:32.916768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.403721Z digest=sha256:1262ac735fd0d29f2b15448d5f45390e34688a64cbb7f4455a6e3c7194f3268c

Observation 2ea84275-2bd1-4bf5-8115-1b77ea8725e9 · outbound

This paper cites Grasp pose detection in point clouds,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Grasp pose detection in point clouds,

Reference 14

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raw_fallback, observed 2026-08-06T15:51:32.727990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.460833Z digest=sha256:e80a7aa91bde493f254157eba282410fbf7b9e780981db9c7f2000cb54bc7e1a

Observation 14ef0bd4-b203-4e93-8201-bc2b391b8a03 · outbound

This paper cites Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:32.482899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.538005Z digest=sha256:122bcf545505ebd74b4dc3bbcab7b07670a5bde630efce35359600ea94c58df8

Observation 7696e84f-0676-4063-a642-0b08b584e593 · outbound

This paper cites Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach

Reference 16

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no resolver link, observed 2026-08-06T15:51:25.595782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:25.595782Z digest=sha256:b99294c17d3f3c1a81ef81cf31ac16a04b70e4be10b8594ef5d92de10b515331

Observation de075c3b-a782-4a97-b2d6-3b0628ff75a9 · outbound

This paper cites 6dof grasp planning by optimizing a deep learning scoring function,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning 6dof grasp planning by optimizing a deep learning scoring function,

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T15:51:32.275719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.697901Z digest=sha256:71378f165a057198a684e0bec711a71fb25e283931d2b0263905ba4c9ec9380b

Observation f0341867-1088-4652-a13d-0dd2d09d5dd9 · outbound

This paper cites High precision grasp pose detection in dense clutter,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning High precision grasp pose detection in dense clutter,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:32.056231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.765557Z digest=sha256:fada4920449259b69909b765fafaeb0ffa2eb47e95703be247fea103159e780a

Observation 9acf7f0b-d3ed-4585-b458-7102c4e555b3 · outbound

This paper cites Pointnetgpd: Detecting grasp configurations from point sets,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Pointnetgpd: Detecting grasp configurations from point sets,

Reference 19

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raw_fallback, observed 2026-08-06T15:51:31.845387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.872099Z digest=sha256:7a5ed85b40950c928c5e8e21ccbdd254d5ff7c417dc3af36aef0209c609fce14

Observation 68dc3caf-94e0-4591-b362-71f9161b7b50 · outbound

This paper cites Da 2 dataset: Toward dexterity-aware dual- arm grasping,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Da 2 dataset: Toward dexterity-aware dual- arm grasping,

Reference 20

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raw_fallback, observed 2026-08-06T15:51:31.719478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:25.912645Z digest=sha256:1a3ca54ccfe0c72df8a7ef8c1f18080f5bc64bb894f545730aee0b4a591398b4

Observation 0ea9a593-9cc9-443f-afac-bf727267c045 · outbound

This paper cites Grasping in the wild: Learning 6dof closed-loop grasp- ing from low-cost demonstrations,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Grasping in the wild: Learning 6dof closed-loop grasp- ing from low-cost demonstrations,

Reference 21

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raw_fallback, observed 2026-08-06T15:51:31.528635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.010833Z digest=sha256:f03d07542abec0a48d4fb9d0f6ab8766fc59803d279337cb9492558f4d701a95

Observation 19ab9ec7-c66c-4216-a1f4-d94cadd19462 · outbound

This paper cites Learning synergies between pushing and grasping with self- supervised deep reinforcement learning,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Learning synergies between pushing and grasping with self- supervised deep reinforcement learning,

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:26.087163Z digest=sha256:9ed0f5940ff49745317ceb92e6eca7be7993062b8cf4495d9f59f85fe6623c01

Observation 29b05773-f683-4e92-b524-10f9adc6a477 · outbound

This paper cites Reinforcement learning based pushing and grasping objects from ungraspable poses,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Reinforcement learning based pushing and grasping objects from ungraspable poses,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:31.405188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.190056Z digest=sha256:7a656a0c8a316b37157d360a04900e60f70b7f28231cfefd2120c5cb6a7ec190

Observation e5bebfcd-8fe8-41af-85f3-718521fa6594 · outbound

This paper cites Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:31.273672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.233353Z digest=sha256:cfc1aebd5fd24912367be857f30dfd03234425e50769f44fc1290dd266f1dd27

Observation 7ef47b81-4f72-43c2-acad-8d2ed7b29f64 · outbound

This paper cites Learning dexterous manipulation from exemplar object trajectories and pre-grasps,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Learning dexterous manipulation from exemplar object trajectories and pre-grasps,

Reference 25

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raw_fallback, observed 2026-08-06T15:51:31.113549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.338941Z digest=sha256:d8825b4be273b0d8c4f447276e891b66eb9d803f3374d21b95327749c2c11f45

Observation 8ffb7bec-859b-4829-8d56-212ad1ec2f13 · outbound

This paper cites Contact- graspnet: Efficient 6-dof grasp generation in cluttered scenes,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Contact- graspnet: Efficient 6-dof grasp generation in cluttered scenes,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:30.968922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.458114Z digest=sha256:c46799f43dd196c8bb9c809b00d2e318fb11c7d664b2ab73475bb0170a4e3590

Observation 7251a38d-9db3-45b9-9e8b-c753a30799ca · outbound

This paper cites kpam: Keypoint affordances for category-level robotic manipulation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning kpam: Keypoint affordances for category-level robotic manipulation,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:30.837974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.543870Z digest=sha256:0ae1ae6b0079eb0af73b632c3e445dce4cf0c180b1e1bd5fbb29d76180a8c847

Observation 136c7322-f89a-4601-b695-0ffc077742b4 · outbound

This paper cites A data-driven statistical frame- work for post-grasp manipulation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning A data-driven statistical frame- work for post-grasp manipulation,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-06T15:51:30.681619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.608182Z digest=sha256:b0bfaf685fc129a50de79b6a67cf05c449966542d36370d2ce51bad1c127658a

Observation 192c86e1-5119-42f6-85a4-b097cbaac8c2 · outbound

This paper cites Control-based grasp planning with contact points,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Control-based grasp planning with contact points,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:30.516977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.653937Z digest=sha256:1d2abbad447c83ab5dc9e0f362cb69c36a21284fbe5443eb7c7b60539af5939d

Observation fef44323-bb7b-4ba0-b730-d8512e1254f0 · outbound

This paper cites Epro- pnp: Generalized end-to-end probabilistic perspective-n-points for monocular object pose estimation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Epro- pnp: Generalized end-to-end probabilistic perspective-n-points for monocular object pose estimation,

Reference 30

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raw_fallback, observed 2026-08-06T15:51:30.325435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.760045Z digest=sha256:d3eefb3ce1f465b4d2f702152e163a0589762d3811d76cab390f1919394dba22

Observation 0b539156-08b3-4bef-ba43-8daf91f56dba · outbound

This paper cites Adaptive multiple importance sampling,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Adaptive multiple importance sampling,

Reference 31

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raw_fallback, observed 2026-08-06T15:51:30.144160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.817659Z digest=sha256:2731ae5c661f44235a23ac1fcf24b18d0977013d5deb6ed1955510b06bcc0493

Observation 0708f4d8-9dea-4ddc-8210-bf4b232bbe90 · outbound

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

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Epnp: An accurate o(n) solution to the pnp problem,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.992131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.893391Z digest=sha256:3be4d01ab1c46313e3f4b4cc70ecffb0e04b5ec8725fcc03d220eaa3509f5e9e

Observation b5d49cd9-e956-426b-a302-316ff5e2d67a · outbound

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

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Normalized object coordinate space for category-level 6d object pose and size estimation,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.860237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:26.996858Z digest=sha256:b7c93ba29eebc3ece11e1ab7b9c85cec9444406cdc61cd1ebdd3ec95c57ebd48

Observation 7a7318b0-dc70-49ad-85c8-78dba843ef5d · outbound

This paper cites Secondpose: Se (3)-consistent dual-stream feature fusion for category-level pose estimation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Secondpose: Se (3)-consistent dual-stream feature fusion for category-level pose estimation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.712635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.076218Z digest=sha256:648c80ba33d725d7196e6f04e1ed57e5766074a717631f59c579f1fcda0a2cd9

Observation 25525825-f1d0-4070-b2c4-8a67f139bf41 · outbound

This paper cites End-to-end learnable geometric vision by backpropagating pnp optimization,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning End-to-end learnable geometric vision by backpropagating pnp optimization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.556866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.159056Z digest=sha256:d6fe5ebb4ba4401061712d996303fbb1f229ba8a80db43f799b2e58db6b6f61b

Observation d1cabde1-befa-4b5a-b718-b42d4aaf19bc · outbound

This paper cites Deep layer aggrega- tion,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Deep layer aggrega- tion,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.447675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.221307Z digest=sha256:356116ced567980d9d426e746938ead4315168ea47561b3129701d4affd2edc4

Observation 62ad5247-f1af-4d5c-b9e6-770c61ad472c · outbound

This paper cites Deformable convolutional networks,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Deformable convolutional networks,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T15:51:27.303647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:27.303647Z digest=sha256:e7f305f016d14cf4ef15715d8d6da8b5b881d800506bdd207d4f862eb3d7b2ac

Observation 84ce6497-f188-4bf1-8c6a-5a868b4ac7bd · outbound

This paper cites 6-dof graspnet: Variational grasp generation for object manipulation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning 6-dof graspnet: Variational grasp generation for object manipulation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.267344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.372393Z digest=sha256:d0992298effe0bc1b4f5f9563b0ad8b553f296b0313c037b0f596160e7cb46d8

Observation 02ceefd9-b618-4c95-9a6c-2b74eefe749b · outbound

This paper cites Learning 6-dof grasping interaction via deep geometry- aware 3d representations,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Learning 6-dof grasping interaction via deep geometry- aware 3d representations,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:29.124832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.433231Z digest=sha256:a6c4ff5f17aa601f4672419ed4468415a12792659c8d8effd96f947713da7c90

Observation 1ebe97a7-41fc-4867-9209-179d22152726 · outbound

This paper cites Jacquard: A large scale dataset for robotic grasp detection,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Jacquard: A large scale dataset for robotic grasp detection,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:28.928109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.525838Z digest=sha256:b3b262ed9483226af521113085462b4824584bbc77ad8d1125fbb70251f51a9c

Observation b09d5df3-dbb2-4602-8a82-3e8971019e1c · outbound

This paper cites Primitive Shape Recognition for Object Grasping.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Primitive Shape Recognition for Object Grasping

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:51:28.193165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.633994Z digest=sha256:ffddbf224814a34c503fe6da917ec7a20b4a1c4b013e7d0359e6f852eb66733a

Observation f65c6ccc-9d4c-444b-8491-89fc585330a5 · outbound

This paper cites PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T15:51:27.714865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:51:27.714865Z digest=sha256:1759ed05f23fe7aee7ee59b36d9402d8e02fd903e09d3de00d01d1f3422ef51e

Observation 7ce45da3-bac1-409d-bede-ec187a6b625e · outbound

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

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Catgrasp: Learning category-level task-relevant grasping in clutter from simulation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:28.798776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.770725Z digest=sha256:39d19c13b9b819d36483a09a7028f2f5a3c92696dfc7d55d8dd81b2d514a0870

Observation bf1f76f7-86e5-40e1-bbcb-08ace4aa8ca2 · outbound

This paper cites 6d robotic grasping system using convolutional neural networks and adaptive artificial potential fields with orientation control,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning 6d robotic grasping system using convolutional neural networks and adaptive artificial potential fields with orientation control,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:28.664377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.826973Z digest=sha256:778eaa6889381d8b392712625c3930d30a46f010cb6586ce5305ec615a66d61e

Observation 4ba6157e-9da9-4b49-84d0-b5f3cbd59419 · outbound

This paper cites Centergrasp: Object-aware implicit representation learning for simultaneous shape reconstruction and 6-dof grasp estimation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Centergrasp: Object-aware implicit representation learning for simultaneous shape reconstruction and 6-dof grasp estimation,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:28.534199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.893947Z digest=sha256:6e0216cc8b88b23fa4f3eeef5d1938fdf9ccab0d41290aa979e083aed5ad1543

Observation edf57188-9b61-4b5d-a62d-a2b8f1969a6e · outbound

This paper cites Acronym: A large-scale grasp dataset based on simulation,.

KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning Acronym: A large-scale grasp dataset based on simulation,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:51:28.380428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T15:51:27.979467Z digest=sha256:cd7b38b969ec1577de380f7578ecfb894a1dd1d729f669726dfc9aefb554c691

Pith citing papers

No inbound Pith citation observations are available.