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Paper Citation Record · LEDGER

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles

As of 13 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2411.17432.

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

pith.paper-citation-record.v1
2411.17432 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:13:55.208210Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy37
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b97a071-4136-462b-867b-90a1fd1136f1 · outbound

This paper cites Simultaneous localization, mapping and moving object tracking,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Simultaneous localization, mapping and moving object tracking,

Reference 1

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no resolver link, observed 2026-08-12T12:13:54.839352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e4137909-9df0-4df8-86a9-371c727bad34 · outbound

This paper cites DynaSLAM II: Tightly-coupled multi-object tracking and SLAM,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles DynaSLAM II: Tightly-coupled multi-object tracking and SLAM,

Reference 2

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no resolver link, observed 2026-08-12T12:13:54.849531Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:54.849531Z digest=sha256:c83330f5cf93a98734ffdf2ac65649d573dbb405e34e2ddfaaaef8317ede26fd

Observation 18ea0b79-aa1f-4a1b-b1fd-dd4a44fa79b6 · outbound

This paper cites DL-SLOT: Tightly- coupled dynamic LiDAR SLAM and 3D object tracking based on collaborative graph optimization,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles DL-SLOT: Tightly- coupled dynamic LiDAR SLAM and 3D object tracking based on collaborative graph optimization,

Reference 3

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no resolver link, observed 2026-08-12T12:13:54.855778Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:54.855778Z digest=sha256:fc7cf7edeb11a356d6ff91241292c110fbf94951f38090d528d8b8222b463e7e

Observation 711e441e-00d4-4a1f-8a41-157d0d1c82be · outbound

This paper cites IMM-SLAMMOT: Tightly-coupled SLAM and IMM-based multi-object tracking,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles IMM-SLAMMOT: Tightly-coupled SLAM and IMM-based multi-object tracking,

Reference 4

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no resolver link, observed 2026-08-12T12:13:54.861732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:54.861732Z digest=sha256:80f93c8c8aa5027e4805b47eca10aa9b3c2e44c1161e6f6c98a4f59ca180ca1c

Observation 6528c106-b3f2-4637-88c8-c6d6d8f42df8 · outbound

This paper cites Multi-vehicle cooperative perception and augmented reality for driver assistance: A possibility to see through front vehicle,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Multi-vehicle cooperative perception and augmented reality for driver assistance: A possibility to see through front vehicle,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.540791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.869079Z digest=sha256:9e035289d524210a714ca277acc179db5cc32c03adc0c087894808c536858b58

Observation 4b677379-5cbb-481e-a576-645487a8ebf4 · outbound

This paper cites Multi-vehicle cooperative local mapping: A methodology based on occupancy grid map merging,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Multi-vehicle cooperative local mapping: A methodology based on occupancy grid map merging,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.509677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.875072Z digest=sha256:55a461c02b9c39e95d24980458e12360e84bd7c0c33c7377e640cb3cbe53fadf

Observation 20cb4876-5f22-45fc-a5f8-5e1c50adc134 · outbound

This paper cites Cooperative multi-vehicle localization using split covariance intersection filter,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Cooperative multi-vehicle localization using split covariance intersection filter,

Reference 7

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raw_fallback, observed 2026-08-12T12:13:56.479090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.882637Z digest=sha256:ccd1fc26e49c97987b61dc4b869ceed0d8de68874dbc9b2fbee2df9cfbf17617

Observation 3b261e31-6c5d-40e9-b558-195c2e83f654 · outbound

This paper cites LiDAR SLAM based multi-vehicle cooperative localization using iterated split CIF,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles LiDAR SLAM based multi-vehicle cooperative localization using iterated split CIF,

Reference 8

Resolution
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raw_fallback, observed 2026-08-12T12:13:56.450375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.888516Z digest=sha256:d409e04373d3015d5b7d7bb019a2d5fbc127b265dc3b0a89951ad50eb18459fc

Observation 0456035e-54e9-4242-b022-120f04a9a919 · outbound

This paper cites V2VNet: Vehicle-to-vehicle communication for joint perception and prediction,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles V2VNet: Vehicle-to-vehicle communication for joint perception and prediction,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.416804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.896521Z digest=sha256:f31b4fccb9d9bf33c4480cb8b12a96085f504902fc442814eb504ec4a120a344

Observation 4d037541-d69a-4930-9910-863c44f793da · outbound

This paper cites CoBEVT: Coop- erative bird’s eye view semantic segmentation with sparse transformers,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles CoBEVT: Coop- erative bird’s eye view semantic segmentation with sparse transformers,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.376073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.907257Z digest=sha256:2beacdff1c295403b764ccb66a6e3f0e3e0dcd56002ab8628c7d631a418c714a

Observation 61223c74-48b6-4b00-bee7-85a149aee1c8 · outbound

This paper cites Vehicular communica- tions for ITS: Standardization and challenges,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Vehicular communica- tions for ITS: Standardization and challenges,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.337849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.913322Z digest=sha256:47c226321b1a456022184160b0d4ec097f1cd2aaf66c151235945c3a25c16d57

Observation f6db84b6-0d5a-45d6-bb83-aa5e507de171 · outbound

This paper cites A cooperative localization-aided tracking algorithm for THz wireless systems,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles A cooperative localization-aided tracking algorithm for THz wireless systems,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.313796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.921516Z digest=sha256:da4ef6871a83c00c03aaa77ec828a23c83bea344afc6091531a5e243b6647eed

Observation 5960acce-8b32-437a-9962-ed73536ad08c · outbound

This paper cites Cooperative perception and localization for cooperative driving,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Cooperative perception and localization for cooperative driving,

Reference 13

Resolution
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raw_fallback, observed 2026-08-12T12:13:56.289862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.928762Z digest=sha256:ae97ec6373b67665e07d93e5ecae186030445bd1a4af8f3507816370a81f7ebf

Observation 2dbcba5c-f528-4d58-859b-ee563a8a51a9 · outbound

This paper cites Vision-based cooperative simultaneous localization and tracking,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Vision-based cooperative simultaneous localization and tracking,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.264298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.936353Z digest=sha256:5416f8262bb9ce19cb7e5a61a82e412406491f46889ad2289699dc7b33211360

Observation 2bbd4323-7607-41f5-83ba-3ded249c3fe4 · outbound

This paper cites Exploiting moving objects: Multi-robot simultaneous localization and tracking,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Exploiting moving objects: Multi-robot simultaneous localization and tracking,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.220854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.942599Z digest=sha256:a760986f35a17ec66cf7275dc6b0c693979f754f58537b9f90303db03ef027ff

Observation 6d71a36b-d492-4d5b-a6e4-3579582a1dcc · outbound

This paper cites Multi-vehicle cooperative simultaneous LiDAR SLAM and object tracking in dynamic environments,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Multi-vehicle cooperative simultaneous LiDAR SLAM and object tracking in dynamic environments,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:54.959829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:54.959829Z digest=sha256:2ae2a8daa01c5201eb785a9dd9db12aa305050e325727043927f86d6ff8b1314

Observation dbfbfc6d-ee34-4571-9d5d-c9bb93a02660 · outbound

This paper cites RDC- SLAM: A real-time distributed cooperative SLAM system based on 3D LiDAR,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles RDC- SLAM: A real-time distributed cooperative SLAM system based on 3D LiDAR,

Reference 17

Resolution
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raw_fallback, observed 2026-08-12T12:13:56.169857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.969226Z digest=sha256:081e05c9e5cc838b589cfdfddc18cf029d2e172c695fc5be920440a59e3ca00c

Observation 962a28b0-2a98-41c9-b8a5-d434c2a5003a · outbound

This paper cites Where2comm: Communication-efficient collaborative perception via spatial confidence maps,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Where2comm: Communication-efficient collaborative perception via spatial confidence maps,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.147719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.977737Z digest=sha256:0c728cda6c35d56cff12635bd6f22f6b867a71046ffba51965b7a2f18193a39a

Observation e48ff223-2c31-4a9d-8287-809d36163090 · outbound

This paper cites Cooperative localization and multi-target tracking in agent networks with the sum- product algorithm,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Cooperative localization and multi-target tracking in agent networks with the sum- product algorithm,

Reference 19

Resolution
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raw_fallback, observed 2026-08-12T12:13:56.126811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.985855Z digest=sha256:670a63db7011410345f18fb45664b30cf77097d4f5b0fabd1b77e886b34f9899

Observation d172ec1c-12e6-4bf5-8651-e88b0d5efb17 · outbound

This paper cites Survey on ranging sensors and cooperative tech- niques for relative positioning of vehicles,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Survey on ranging sensors and cooperative tech- niques for relative positioning of vehicles,

Reference 20

Resolution
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raw_fallback, observed 2026-08-12T12:13:56.102091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:54.999860Z digest=sha256:cec446cf59c78de2dd9380650b7d615e81779eba2aa5fc9e23cebbf84fcb875f

Observation d2164f3a-b285-43f3-919a-fc5f9219a491 · outbound

This paper cites A collaborative relative localization method for vehicles using vision and LiDAR sensors,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles A collaborative relative localization method for vehicles using vision and LiDAR sensors,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.066283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.009825Z digest=sha256:aadffa35e68ee9e9d8e3d3517f84ad0d574f5a755cb7231ccb57917dde940339

Observation 437e29f5-5d31-40e5-bc35-ea1d8a7197ac · outbound

This paper cites Recursive decentralized localization for multi-robot systems with asynchronous pairwise communication,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Recursive decentralized localization for multi-robot systems with asynchronous pairwise communication,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.040163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.020746Z digest=sha256:de0147c7d8bd75f576f7a1f98a19411bb0ff7ed5f0e5dcdc084ef5aa820ff572

Observation 2e4f39ef-0a36-40dd-b602-f25e5530f745 · outbound

This paper cites Delight: An efficient descriptor for global localisation using LiDAR intensities,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Delight: An efficient descriptor for global localisation using LiDAR intensities,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:56.015937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.029140Z digest=sha256:9354441d0ebb239974de77f02c5b54713095f02bef5152ca04528a0ecea961db

Observation 805a242e-7e1b-418b-9d99-d0f5c24d69ad · outbound

This paper cites SegMap: Segment-based mapping and localization using data-driven descriptors,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles SegMap: Segment-based mapping and localization using data-driven descriptors,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.983058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.042328Z digest=sha256:621642d3cf7183d0ec5b63ef3038fc0e639942f7bc9106ddb2236951a4273e92

Observation be44f35c-a125-4b5e-a651-c4c246ad920a · outbound

This paper cites Fast point feature histograms (FPFH) for 3D registration,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Fast point feature histograms (FPFH) for 3D registration,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.961760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.047775Z digest=sha256:7caeef4ae1478d9af94467a13ff7e31fdd106140880f1dbeeedb20d4c7f55896

Observation 11458702-5dd6-40a8-b085-864216490421 · outbound

This paper cites PointNetVLAD: Deep point cloud based retrieval for large-scale place recognition,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles PointNetVLAD: Deep point cloud based retrieval for large-scale place recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.934893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.053226Z digest=sha256:1e8a6cd60abc668a8f8ea4da45bf6384a7f22247cfe29a0faf418039cc7c8088

Observation 90cb0adf-0860-4794-884c-b01cf978f82a · outbound

This paper cites Netvlad: CNN architecture for weakly supervised place recognition,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Netvlad: CNN architecture for weakly supervised place recognition,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.908452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.059291Z digest=sha256:f9211c8365334a3a8b17585173a837a9defaa0fe658473c30238c34bdf4ca0a5

Observation 6aa0c225-c5db-4f71-8873-7c6d1029aa12 · outbound

This paper cites Scan context: Egocentric spatial descriptor for place recognition within 3D point cloud map,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Scan context: Egocentric spatial descriptor for place recognition within 3D point cloud map,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.882322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.067752Z digest=sha256:c85a19d95ee1f3c8eb9f9b8eb019eab56088b4409ddd6e7820d06f93461f3039

Observation 3e1d3041-7841-4715-8561-fc5a3e90cbe7 · outbound

This paper cites Intensity scan context: Coding intensity and geometry relations for loop closure detection,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Intensity scan context: Coding intensity and geometry relations for loop closure detection,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.842244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.072640Z digest=sha256:fe6991ebdc3d8459b97c2ae545622ce98536bbb4154c63f61549e8a05b3ce5e8

Observation 9365cea2-dccf-4f97-93a3-a6c2f254b07f · outbound

This paper cites Learning sequential descriptors for sequence-based visual place recognition,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Learning sequential descriptors for sequence-based visual place recognition,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.784862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.080866Z digest=sha256:c22145c5649a6924055db421806624d139f019d0f51555a19ac961b6602b3ff7

Observation af8bd89b-e0ef-4dc3-8a6e-9437b05c8dd5 · outbound

This paper cites Learning sequence descriptor based on spatio-temporal attention for visual place recognition,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Learning sequence descriptor based on spatio-temporal attention for visual place recognition,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.754769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.090614Z digest=sha256:e3cb33895d52cfbb34f8ce5e563fff5c8d1c07a4f7b71eb86cd48234dfe03c4c

Observation 4b6bdbd2-eb24-4c9d-b3c2-981fbd9335f1 · outbound

This paper cites Distinctive image features from scale-invariant keypoints,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Distinctive image features from scale-invariant keypoints,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.722589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.095747Z digest=sha256:8b0365dba3b86a0b68812db051d4f8cf3e9feb5c83aca05de71cb12dfefcb864

Observation 9663da15-250a-48a7-94fb-2ff1e97ee23c · outbound

This paper cites ORB: An efficient alternative to SIFT or SURF,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles ORB: An efficient alternative to SIFT or SURF,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.696234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.103448Z digest=sha256:162df300424a024c36933849f8d3c709fa104c3c50f9128563366387489893f1

Observation e91055e4-39b7-457c-a333-137f9d299898 · outbound

This paper cites Superpoint: Self- supervised interest point detection and description,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Superpoint: Self- supervised interest point detection and description,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.672152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.109821Z digest=sha256:ce709e6e2665533db25ead77e68441f0b3663f2be6d6e88717465f1ea9de2bcf

Observation 1881fb2a-0a68-485c-b91b-ed4bfd50b700 · outbound

This paper cites Who2com: Collaborative perception via learnable handshake communi- cation,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Who2com: Collaborative perception via learnable handshake communi- cation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.630620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.114877Z digest=sha256:a24e1deba70689a0f886184dcdc83a694766bb5e318b048913e0ba79ccaf19ae

Observation 2ea8d9f3-a63a-4e64-846f-71c6655d5aee · outbound

This paper cites When2com: Multi-agent per- ception via communication graph grouping,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles When2com: Multi-agent per- ception via communication graph grouping,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.606756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.125387Z digest=sha256:39a583346c3d81886dbbd85478ad8fb698b8a829861667a9d77a99363f71a7af

Observation d76f9038-657a-4304-9585-e63344c12546 · outbound

This paper cites Learning distilled collaboration graph for multi-agent perception,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Learning distilled collaboration graph for multi-agent perception,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.133626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.133626Z digest=sha256:f8425c595b3d1b24d315c5b3e8e7e6002f32a0f7bc482c9bd8ae7221ebd961b5

Observation 57b9fbca-af47-465a-b834-a4c16d307ca0 · outbound

This paper cites LeGO-LOAM: Lightweight and ground- optimized LiDAR odometry and mapping on variable terrain,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles LeGO-LOAM: Lightweight and ground- optimized LiDAR odometry and mapping on variable terrain,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.139651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.139651Z digest=sha256:00db8f42e38c532f9bd78d4daea0192f05ea1ae100ae0122577c7aba69346466

Observation d89425e1-a9c1-4ecd-bb88-8ee0a72c7bb3 · outbound

This paper cites Low-drift and real-time LiDAR odometry and mapping,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Low-drift and real-time LiDAR odometry and mapping,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.148315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.148315Z digest=sha256:fe4b9071f69014cc2cb5ac506e22cfe953d8e2f73148b7413bb257581e31be73

Observation 2c8622c8-dfcb-4f5a-af2c-bcfb5c9239d3 · outbound

This paper cites A review of LiDAR radiometric processing: From ad hoc intensity correction to rigorous radiometric calibration,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles A review of LiDAR radiometric processing: From ad hoc intensity correction to rigorous radiometric calibration,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.502576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.154847Z digest=sha256:93bcbd518ed02c6352a99eab2c52891a88d56f015768be8ea182a179b97a5f70

Observation 29d7d2f0-d99f-4b4b-b6cf-7ebe268c3554 · outbound

This paper cites Superglue: Learning feature matching with graph neural networks,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Superglue: Learning feature matching with graph neural networks,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.475706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.160508Z digest=sha256:bc1990b1552576ebecac2ee6ddf356209a1a6739845f12c488b903757b8c23cc

Observation 62e9ad17-2a01-410f-a212-aa38b801fc6b · outbound

This paper cites OPV2V: An open benchmark dataset and fusion pipeline for perception with vehicle-to- vehicle communication,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles OPV2V: An open benchmark dataset and fusion pipeline for perception with vehicle-to- vehicle communication,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.442411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.165754Z digest=sha256:849ffddaad9e3efffc997c72c7e898a76e6c3bdbb14c56c9e0c839a479a2c0e1

Observation ae4efcdb-332a-4295-b992-b9f049f78aee · outbound

This paper cites V2V4Real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles V2V4Real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.413816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.177362Z digest=sha256:8b36bdc047865032646b0eaffe5af192d77aff99bc93975142929e8870f4d049

Observation 76247bf3-3deb-4dcd-a7cd-1cf75d07935e · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Pointpillars: Fast encoders for object detection from point clouds,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.391035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.186990Z digest=sha256:4f8d8637a645dcb9b38766f88111be485ce532564da62cc22f073e6e187aa675

Observation 85ec5563-d2b2-4504-821f-e2e2965fa6ae · outbound

This paper cites Asynchronous state estimation of simultaneous ego-motion estimation and multiple object tracking for LiDAR-inertial odometry,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Asynchronous state estimation of simultaneous ego-motion estimation and multiple object tracking for LiDAR-inertial odometry,

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.193484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.193484Z digest=sha256:3872a3068aae906d1f26d2833347bb5e920d9a8652dc267ce6d40d75082d3cef

Observation d478d67b-2f9d-4718-9fa7-108c2822852b · outbound

This paper cites Factor graph based 3D multi- object tracking in point clouds,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Factor graph based 3D multi- object tracking in point clouds,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:55.201211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:55.201211Z digest=sha256:8f094e45b79647a53380c48239081c53a9b9795b10f0c1e78a732b80a61f428d

Observation 69c3684b-3017-43c8-80d0-a154f67096b3 · outbound

This paper cites Adaptive cubature split covariance inter- section filter for multi-vehicle cooperative localization,.

Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles Adaptive cubature split covariance inter- section filter for multi-vehicle cooperative localization,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:13:55.305721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T12:13:55.208210Z digest=sha256:6d1930f5bda3d174076ee9824cfbcd35f38d3bf66adb520286df1f9b1d75c7ee

Pith citing papers

No inbound Pith citation observations are available.