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Paper Citation Record · LEDGER

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions

As of 22 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2501.07133.

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

pith.paper-citation-record.v1
2501.07133 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:04.932994Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

50 of 50 outbound references displayed

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  • verified fuzzy37
  • unresolved11
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d5418347-3881-4ef8-9f2f-5e4912fd31dc · outbound

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

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 1

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Source-reported events for the cited work

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Observation b5e1c03c-7819-4f20-8fbb-c6d29238ece5 · outbound

This paper cites P2b: Point-to- box network for 3d object tracking in point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions P2b: Point-to- box network for 3d object tracking in point clouds,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 92b05e0a-5e45-4afc-b496-4e2eb8db0efa · outbound

This paper cites 3d siamese voxel-to- bev tracker for sparse point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions 3d siamese voxel-to- bev tracker for sparse point clouds,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 61a30395-40b8-4c4a-8211-3d9b1e5d9f44 · outbound

This paper cites Pttr: Relational 3d point cloud object tracking with transformer,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Pttr: Relational 3d point cloud object tracking with transformer,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 704b46af-2fb3-4f16-b785-061739bb061c · outbound

This paper cites Osp2b: One- stage point-to-box network for 3d siamese tracking,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Osp2b: One- stage point-to-box network for 3d siamese tracking,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation db74c5df-af08-409f-8652-e576347303a5 · outbound

This paper cites Glt-t: Global-local transformer voting for 3d single object tracking in point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Glt-t: Global-local transformer voting for 3d single object tracking in point clouds,

Reference 6

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Observation 07eab134-2f85-432b-ab59-8fed6ab7e299 · outbound

This paper cites Attention is all you need,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Attention is all you need,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 31d46889-83bd-4a0a-ab3f-9f6303c7da0f · outbound

This paper cites 3d siamese transformer network for single object tracking on point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions 3d siamese transformer network for single object tracking on point clouds,

Reference 8

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raw_fallback, observed 2026-08-10T20:53:05.750033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation dd1830fc-f69f-4278-b355-03ef15d6b4ed · outbound

This paper cites Ost: Efficient one- stream network for 3d single object tracking in point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Ost: Efficient one- stream network for 3d single object tracking in point clouds,

Reference 9

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raw_fallback, observed 2026-08-10T20:53:05.733467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3a516fa3-9d21-4689-986b-d8d16727d47b · outbound

This paper cites Dgcnn: A convolutional neural network over large-scale labeled graphs,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Dgcnn: A convolutional neural network over large-scale labeled graphs,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a5bb2b8b-2d9a-486f-b1f6-2b2677170898 · outbound

This paper cites Mbptrack: Improving 3d point cloud tracking with memory networks and box priors,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Mbptrack: Improving 3d point cloud tracking with memory networks and box priors,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6a57c08d-8795-491b-8b9f-42d21dc714ee · outbound

This paper cites Cxtrack: Improving 3d point cloud tracking with contextual information,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Cxtrack: Improving 3d point cloud tracking with contextual information,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fefb6985-96de-47cf-a490-261f1f3592ee · outbound

This paper cites Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 91b1d027-a07b-41d8-a002-d2f780a988a3 · outbound

This paper cites Learning the incremental warp for 3d vehicle tracking in lidar point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Learning the incremental warp for 3d vehicle tracking in lidar point clouds,

Reference 14

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raw_fallback, observed 2026-08-10T20:53:05.664646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0be937d0-a543-47a6-a6db-5786f15f5bab · outbound

This paper cites Point cloud registration-driven robust feature matching for 3-d siamese object tracking,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Point cloud registration-driven robust feature matching for 3-d siamese object tracking,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.647582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5846e3f0-6e17-4d85-b207-05a64563a778 · outbound

This paper cites Benchmarking neural network ro- bustness to common corruptions and perturbations,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Benchmarking neural network ro- bustness to common corruptions and perturbations,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 71c6535d-6f73-4eae-88f3-362f468029b7 · outbound

This paper cites Exploring implicit domain-invariant features for domain adaptive object detection,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Exploring implicit domain-invariant features for domain adaptive object detection,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 77cf6e79-08e6-4e3f-9ab3-373835c49e97 · outbound

This paper cites Dynamics-aware adversarial attack of adaptive neural networks,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Dynamics-aware adversarial attack of adaptive neural networks,

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.596427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0376f261-a750-4f88-a6e2-59a3e3fe8ac3 · outbound

This paper cites Only once attack: Fooling the tracker with adversarial template,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Only once attack: Fooling the tracker with adversarial template,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d56a6ce8-f752-42d1-b355-1ed3905ede1f · outbound

This paper cites Conda: Unsupervised domain adaptation for lidar segmentation via regularized domain concatenation,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Conda: Unsupervised domain adaptation for lidar segmentation via regularized domain concatenation,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f63576c0-e07a-4839-85a1-c1e23beb576b · outbound

This paper cites Revisiting open world object detection,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Revisiting open world object detection,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a42de574-fbec-4f39-8256-f256a5b2f13c · outbound

This paper cites Consensus synergizes with memory: A simple approach for anomaly segmentation in urban scenes,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Consensus synergizes with memory: A simple approach for anomaly segmentation in urban scenes,

Reference 22

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raw_fallback, observed 2026-08-10T20:53:05.530662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2344c121-2580-4850-bc15-85091ba8ebfd · outbound

This paper cites Toward class-agnostic tracking using feature decorrelation in point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Toward class-agnostic tracking using feature decorrelation in point clouds,

Reference 23

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raw_fallback, observed 2026-08-10T20:53:05.514550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 23968cc0-bc22-47f0-b495-3b723c1b7a82 · outbound

This paper cites Seeing through fog without seeing fog: Deep multi- modal sensor fusion in unseen adverse weather,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Seeing through fog without seeing fog: Deep multi- modal sensor fusion in unseen adverse weather,

Reference 24

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Observation d9c17ee8-5ecc-410a-a910-38641f8b2657 · outbound

This paper cites Canadian adverse driving conditions dataset,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Canadian adverse driving conditions dataset,

Reference 25

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raw_fallback, observed 2026-08-10T20:53:05.489663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4dc39375-33d9-470f-99ac-a0311b24148e · outbound

This paper cites Ithaca365: Dataset and driving perception under repeated and challenging weather conditions,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Ithaca365: Dataset and driving perception under repeated and challenging weather conditions,

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:04.817716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:04.817716Z digest=sha256:553a1fd9170989af5410c94862a4e9fb7ae78e775ff21488f2f452495bf95b61

Observation 5fa89550-52d3-418b-b82f-199ee4d2649b · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.465665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 60969938-0fbd-4fb9-b0b5-2c3a61147f44 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions nuscenes: A multi- modal dataset for autonomous driving,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.450869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6d5d56c5-1335-4678-a35a-b885fe3cf0cc · outbound

This paper cites Box- aware feature enhancement for single object tracking on point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Box- aware feature enhancement for single object tracking on point clouds,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.434456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.833744Z digest=sha256:7f121869f73b71ef8af6adf46208d22cde5ee1a6988c4c860e87cf12080ce619

Observation 9a6f5ac4-6469-409d-a3c3-927b14f44db6 · outbound

This paper cites 3d object tracking with transformer,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions 3d object tracking with transformer,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.416748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3d81cfba-7620-4c69-a1b5-21fdb271df13 · outbound

This paper cites Ptt: Point-track-transformer module for 3d single object tracking in point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Ptt: Point-track-transformer module for 3d single object tracking in point clouds,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.400360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.843403Z digest=sha256:49be53443ba115b0826eb9a1794a6dfdf9dffb41410285ef5694e434c0e09bb2

Observation 1f7a6682-35f4-4295-99cc-61481a2a40d2 · outbound

This paper cites Deep supervised descent method with multiple seeds generation for 3-d tracking in point cloud,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Deep supervised descent method with multiple seeds generation for 3-d tracking in point cloud,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.384028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.848041Z digest=sha256:f3c4d20ab991b06bada9ac40d12955ecafe7d0ca1e0670c161948ce673cc81b4

Observation 598731d7-6980-49e2-a617-4b5b87ddd33a · outbound

This paper cites Leveraging shape completion for 3d siamese tracking,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Leveraging shape completion for 3d siamese tracking,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.368366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9cfe3055-92f3-4b07-99b2-56c6fde51f68 · outbound

This paper cites Benchmarking the Robustness of LiDAR Semantic Segmentation Models.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Benchmarking the Robustness of LiDAR Semantic Segmentation Models

Reference 34

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Observation 2b1d5d66-33eb-4756-9f69-cff095857fd8 · outbound

This paper cites 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds,

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7291bbaf-dd14-43a9-811b-ba770049909d · outbound

This paper cites Robo3d: Towards robust and reliable 3d perception against corruptions,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Robo3d: Towards robust and reliable 3d perception against corruptions,

Reference 36

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Observation 6082f2ef-125f-4d5e-b494-27379a52dcf2 · outbound

This paper cites Benchmarking robustness of 3d object detection to common corruptions,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Benchmarking robustness of 3d object detection to common corruptions,

Reference 37

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source=pdf_text observed=2026-08-10T20:53:04.871823Z digest=sha256:b69e0ebdf48be32bc7fcf3cbfbbdd83753af846d84ff89fa7d802c96faf0b3b8

Observation 15af5ee3-7ed4-427d-8375-1012408d944d · outbound

This paper cites Transfer learning from synthetic to real lidar point cloud for semantic segmentation,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Transfer learning from synthetic to real lidar point cloud for semantic segmentation,

Reference 38

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no resolver link, observed 2026-08-10T20:53:04.876458Z

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source=pdf_text observed=2026-08-10T20:53:04.876458Z digest=sha256:a4c2a5ce3ad7e1eacc24f191ed8d92c9b74a511ef6eb49f90152483569775c9a

Observation e526ec13-b032-4c84-9285-94d030cd56a9 · outbound

This paper cites xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation,

Reference 39

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source=pdf_text observed=2026-08-10T20:53:04.881202Z digest=sha256:c940896995bdb25d46267e1c4f1cdb6fb56bf0558f833326b5b8463f0f3b45dd

Observation 3be7be1b-781b-488b-8028-34aaeaa31164 · outbound

This paper cites Lidar snowfall simulation for robust 3d object detection,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Lidar snowfall simulation for robust 3d object detection,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.317942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ef2adbaf-44c6-40d7-bdeb-f0c6826bbf9b · outbound

This paper cites Fog simulation on real lidar point clouds for 3d object detection in adverse weather,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Fog simulation on real lidar point clouds for 3d object detection in adverse weather,

Reference 41

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no resolver link, observed 2026-08-10T20:53:04.890142Z

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source=pdf_text observed=2026-08-10T20:53:04.890142Z digest=sha256:2f076cb701fce64a114bc4f1d1ccc65d77a33b483c7299fbfa36814f397777d2

Observation f8bead78-df09-47b3-92c8-8cf42a540c2a · outbound

This paper cites Invisible for both camera and lidar: Security of multi- sensor fusion based perception in autonomous driving under physical- world attacks,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Invisible for both camera and lidar: Security of multi- sensor fusion based perception in autonomous driving under physical- world attacks,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.292406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.894856Z digest=sha256:db8acd41454b99503d31d28f2323e82582d50da2cda82a1f393a62802b7cbf74

Observation 9e248a7a-2401-4b6b-88b7-33d62021264f · outbound

This paper cites On the real-world adversarial robustness of real-time semantic segmentation models for autonomous driving,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions On the real-world adversarial robustness of real-time semantic segmentation models for autonomous driving,

Reference 43

Resolution
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source=pdf_text observed=2026-08-10T20:53:04.899488Z digest=sha256:c6547a457d37fce8c8084cf889a87a8555d4d2ec7fe89691b482a2dca6b1ff8f

Observation d9ffa763-f07c-4467-99eb-fef9efbf8806 · outbound

This paper cites De-noising of lidar point clouds corrupted by snowfall,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions De-noising of lidar point clouds corrupted by snowfall,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.266118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.904551Z digest=sha256:cd9614bd3e5deab1e041a0d139656f8dbda5c237f94cfa127f13cba976fce501

Observation d59eb65d-0828-42c3-a438-5234a5267730 · outbound

This paper cites Pointfilternet: A filtering network for point cloud denoising,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Pointfilternet: A filtering network for point cloud denoising,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.248756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.909280Z digest=sha256:98965624415126350210fb54b9d43d231e442d1f4e927ceacdc7b856ef2fd822

Observation 65394d20-cdc4-4aa2-bbaa-ad306810abfe · outbound

This paper cites Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.232567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.913818Z digest=sha256:4617426451c1a1f67b7fc032bccbcf488450f5e43d3f697f60b59ec81ef338b3

Observation 3adfb0b7-d507-4571-aa53-5ab26f9bd41a · outbound

This paper cites LiDAR Snowfall Simulation for Robust 3D Object Detection,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions LiDAR Snowfall Simulation for Robust 3D Object Detection,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.216057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T20:53:04.918459Z digest=sha256:53c0cf5fe358ee6cc17c17382f503cb370c6be71dcb577910aa463fd8986650c

Observation 980576ee-5ae1-4f31-8f13-6e78c728b082 · outbound

This paper cites Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:04.923196Z digest=sha256:24fa6bd0b1af79aecf297d60924b2a34574f001f4300f1e865a2e329bd061d7b

Observation 4964f1ab-95ef-43da-84a7-32da939b8eda · outbound

This paper cites Unimix: Towards do- main adaptive and generalizable lidar semantic segmentation in adverse weather,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Unimix: Towards do- main adaptive and generalizable lidar semantic segmentation in adverse weather,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.198489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 35b0f7f5-f231-4af9-9319-25727a56737c · outbound

This paper cites Domain randomization for transferring deep neural networks from sim- ulation to the real world,.

Robust Single Object Tracking in LiDAR Point Clouds under Adverse Weather Conditions Domain randomization for transferring deep neural networks from sim- ulation to the real world,

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-10T20:53:05.181532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.