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Paper Citation Record · LEDGER

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration

As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2512.21831.

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

pith.paper-citation-record.v1
2512.21831 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:05:26.129241Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

33 of 33 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5e535ae-4cb3-4ed1-aa2f-03f41b6e261b · outbound

This paper cites Cooper: Cooperative perception for connected autonomous vehicles based on 3d point clouds.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Cooper: Cooperative perception for connected autonomous vehicles based on 3d point clouds

Reference 1

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source=pdf_text observed=2026-08-03T14:05:25.857830Z digest=sha256:092c4cde3fb672315d962ad1cbda7a24ef41ef02c79aa4d1ba29e2be9b581dee

Observation 7380cb2e-73a6-4b4c-a3da-bba14b6eb094 · outbound

This paper cites F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds

Reference 2

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source=pdf_text observed=2026-08-03T14:05:25.864958Z digest=sha256:f823ce78734bdefe355315e8f8c5a3a2d4c01f453805eac1e701d429b93cc770

Observation 99b1ae93-8b88-4fb4-9943-dbc32cf3e7e6 · outbound

This paper cites V2vnet: Vehicle-to-vehicle communication for joint perception and prediction.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2vnet: Vehicle-to-vehicle communication for joint perception and prediction

Reference 3

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source=pdf_text observed=2026-08-03T14:05:25.875228Z digest=sha256:9f6eb3ec30b78a5b5498dbb01cb4f6d831e0fc263d93d22d9562b074f8b8f165

Observation d8be1ce7-b349-4c79-aa92-5f4f1de0cf6a · outbound

This paper cites Where2comm: Communication-efficient collaborative perception via spatial confidence maps.Advances in neural information processing systems, 35:4874– 4886, 2022.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Where2comm: Communication-efficient collaborative perception via spatial confidence maps.Advances in neural information processing systems, 35:4874– 4886, 2022

Reference 4

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source=pdf_text observed=2026-08-03T14:05:25.883920Z digest=sha256:0e516be68c867a9758c55382f58c3e7c67f8fbb5628da849332b1a3ebf748c85

Observation 1ddb9fb4-e968-41f2-8ceb-9c32578664cb · outbound

This paper cites V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting

Reference 5

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source=pdf_text observed=2026-08-03T14:05:25.899724Z digest=sha256:37f601b86f11b3617960622e11116fc945f6a99d53e21aad872a6d03e1d070d6

Observation 4b67cfd6-b4ae-4019-b80c-1fcdb12e2565 · outbound

This paper cites V2x-sim: Multi-agent collaborative perception dataset and benchmark for autonomous driving.IEEE Robotics and Automation Letters, 7(4):10914–10921, 2022.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2x-sim: Multi-agent collaborative perception dataset and benchmark for autonomous driving.IEEE Robotics and Automation Letters, 7(4):10914–10921, 2022

Reference 6

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source=pdf_text observed=2026-08-03T14:05:25.909181Z digest=sha256:09e111c28a6acc1414280a52b680997ccfa3deb46292cdb1972e42a03053bd54

Observation 626751cd-e22c-46c5-9227-a8b328768504 · outbound

This paper cites V2v4real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2v4real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception

Reference 7

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source=pdf_text observed=2026-08-03T14:05:25.916727Z digest=sha256:fc08103555f368c933a36d2d21126278955be641ed8fadad33e492c836cdfd2d

Observation 052ddd2b-b378-465f-a5d5-43a90e4fd21a · outbound

This paper cites Advisory warnings based on cooperative perception.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Advisory warnings based on cooperative perception

Reference 8

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source=pdf_text observed=2026-08-03T14:05:25.926199Z digest=sha256:ad3baf6ebbfd04fe96b23f8d99f7077cd1a74803a7103847e7d5785601e088be

Observation b8ed3538-c6d2-4ba1-8307-b33d8ef1e68a · outbound

This paper cites Shared perception for connected and automated vehicles.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Shared perception for connected and automated vehicles

Reference 9

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source=pdf_text observed=2026-08-03T14:05:25.937687Z digest=sha256:4cb8e157223225bc4ab383d96547fef38796d28997e1cba895ab4629cb7c3e6b

Observation 7c19c7b4-f099-4f56-9600-7fa7e8a363c2 · outbound

This paper cites Lidar-based end-to-end temporal perception for vehicle-infrastructure cooperation.IEEE INTERNET OF THINGS JOURNAL, 12(13):22862–22874, JUL 1 2025.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Lidar-based end-to-end temporal perception for vehicle-infrastructure cooperation.IEEE INTERNET OF THINGS JOURNAL, 12(13):22862–22874, JUL 1 2025

Reference 10

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source=pdf_text observed=2026-08-03T14:05:25.945016Z digest=sha256:352cf3593925717a602f9f040030fcbbaca5a07b371451d9d28a7e5eb78c7d83

Observation ff42b8dc-6ff6-4dbd-bb47-c8390a353dfa · outbound

This paper cites Dair-v2x: A large-scale dataset for vehicle-infrastructure cooperative 3d object detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Dair-v2x: A large-scale dataset for vehicle-infrastructure cooperative 3d object detection

Reference 11

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source=pdf_text observed=2026-08-03T14:05:25.949557Z digest=sha256:32ecfe4c25d75c5c03b16cac46dd7c1392783d8d8adb169afb1a628160ef9f24

Observation ef86c1b5-f465-4856-a7ad-dd301a81ed4e · outbound

This paper cites Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication

Reference 12

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source=pdf_text observed=2026-08-03T14:05:25.954456Z digest=sha256:ea94c3ff0833f41d371fc03ddb730aa4a3b5d6245a5c85a3d8cc068c529e8b9d

Observation 0c365c19-1f0e-4c49-8603-0aa768760816 · outbound

This paper cites Pointpainting: Sequential fusion for 3d object detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Pointpainting: Sequential fusion for 3d object detection

Reference 13

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source=pdf_text observed=2026-08-03T14:05:25.960818Z digest=sha256:516a3c8c063868e068a58845b97243d92712473684971239b0a3f3f3abf19492

Observation 0c3eeb1b-50db-4475-b462-d737cf9e7b41 · outbound

This paper cites Centerfusion: Center-based radar and camera fusion for 3d object detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Centerfusion: Center-based radar and camera fusion for 3d object detection

Reference 14

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source=pdf_text observed=2026-08-03T14:05:25.966464Z digest=sha256:1c74f8eb11c9f55e8c8a5d320cca83947223f9425b19a01fb57c031c889289e8

Observation eab653d1-c064-430d-a20c-86217275bdff · outbound

This paper cites Deformable feature aggregation for dynamic multi-modal 3d object detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Deformable feature aggregation for dynamic multi-modal 3d object detection

Reference 15

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source=pdf_text observed=2026-08-03T14:05:25.973682Z digest=sha256:b63b304d0722e70a8a47d7e5cee8da7cca8fc9b330c8c80ef4d35ed853cd703a

Observation 623bdd6b-ef12-47df-b58f-c155b698c34d · outbound

This paper cites Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection

Reference 16

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source=pdf_text observed=2026-08-03T14:05:25.982751Z digest=sha256:c106058862b9bf54081cad93585fe0ced91c7ea03d5601827046882f9e317e2f

Observation 538a457b-b306-46fb-8c0b-996d513aab54 · outbound

This paper cites Transfusion: Robust lidar-camera fusion for 3d object detection with transformers.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Transfusion: Robust lidar-camera fusion for 3d object detection with transformers

Reference 17

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source=pdf_text observed=2026-08-03T14:05:25.999105Z digest=sha256:96ce79e0298f8294f2cd2939ad2555c2674d9667dac11cb3a29e5b877db40a25

Observation 4ba343fa-e803-4eaf-a977-f5ba2260a212 · outbound

This paper cites Futr3d: A unified sensor fusion framework for 3d detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Futr3d: A unified sensor fusion framework for 3d detection

Reference 18

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source=pdf_text observed=2026-08-03T14:05:26.005882Z digest=sha256:a2f5c3a39c1b6e5872b67bf54e8410d5af213944c08a56a4cb04293ea777801f

Observation d1a7a700-612a-4031-8e12-697f7330e294 · outbound

This paper cites Deepinteraction: 3d object detection via modality interaction.Advances in Neural Information Processing Systems, 35:1992–2005, 2022.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Deepinteraction: 3d object detection via modality interaction.Advances in Neural Information Processing Systems, 35:1992–2005, 2022

Reference 19

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source=pdf_text observed=2026-08-03T14:05:26.012276Z digest=sha256:74b69d595ab8d5e7060caca1f8875cb8ade0d61089533e52c9473c2c52c744e7

Observation b8ece418-6fbe-48af-afd7-bbb3c237f0b7 · outbound

This paper cites 4d-net for learned multi-modal alignment.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration 4d-net for learned multi-modal alignment

Reference 20

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source=pdf_text observed=2026-08-03T14:05:26.020664Z digest=sha256:55150a34eeb9ea08aec1531c6917724c6bc7074088a4839070f463b3d1da459e

Observation f0ac154f-a76b-4f07-a8ff-3da5f03a6a85 · outbound

This paper cites Recurrentbev: A long-term temporal fusion framework for multi-view 3d detection.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Recurrentbev: A long-term temporal fusion framework for multi-view 3d detection

Reference 21

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source=pdf_text observed=2026-08-03T14:05:26.027034Z digest=sha256:c61fe1cb43e9f6010606b0a4674248acc724db28c7acc3ae6d96334264711d8b

Observation d7b3cdb5-44ce-4b4f-aba3-d96aa258109b · outbound

This paper cites V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction

Reference 22

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source=pdf_text observed=2026-08-03T14:05:26.032618Z digest=sha256:2771df4111a6e0ebe5dc1e396573521c5003475ccf5c37241ed8b545c5dc2217

Observation 75411713-63e1-4b32-89c9-33bd82dfcd8e · outbound

This paper cites Center-based 3d object detection and tracking.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Center-based 3d object detection and tracking

Reference 23

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source=pdf_text observed=2026-08-03T14:05:26.039271Z digest=sha256:9c362410954a2b563bc117aac3cbc2f3e21a98e9f9dbfe1b159385d284036666

Observation 0e77d5b0-e85a-4b9f-ad6e-8144623ed7a5 · outbound

This paper cites Trackformer: Multi-object tracking with transformers.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Trackformer: Multi-object tracking with transformers

Reference 24

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source=pdf_text observed=2026-08-03T14:05:26.047950Z digest=sha256:d6cfced687abf694b981946e4ccea56b7062ee84bda7ad553a39e453764fdb49

Observation c682c2e0-0079-4eaf-abe5-e1e9914801d6 · outbound

This paper cites Motr: End-to-end multiple-object tracking with transformer.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Motr: End-to-end multiple-object tracking with transformer

Reference 25

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source=pdf_text observed=2026-08-03T14:05:26.055692Z digest=sha256:8c667f0176c83bb4a944d4b10dbd1de772451b5ffab27c0b751f6fe654c91932

Observation ede17023-c9a3-4050-9a13-a9b12f644b5f · outbound

This paper cites Learnable online graph representations for 3d multi-object tracking.IEEE Robotics and Automation Letters, 7(2):5103–5110, 2022.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Learnable online graph representations for 3d multi-object tracking.IEEE Robotics and Automation Letters, 7(2):5103–5110, 2022

Reference 26

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source=pdf_text observed=2026-08-03T14:05:26.060836Z digest=sha256:f638d7fffac0bd385a69fab4e26eeafddd4e6b8d3a77890c003fa2d27a020d5b

Observation 525d15a3-be53-4b66-951d-5a982424922f · outbound

This paper cites Motiontrack: end-to-end transformer- based multi-object tracking with lidar-camera fusion.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Motiontrack: end-to-end transformer- based multi-object tracking with lidar-camera fusion

Reference 27

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source=pdf_text observed=2026-08-03T14:05:26.065994Z digest=sha256:f5c3e09478dbedfddf86760fd9ba20aae1f51ada9a2611ea419d48d6aec07233

Observation e4d85a61-3966-4c70-8ad3-89e1ee766200 · outbound

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

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Pointpillars: Fast encoders for object detection from point clouds

Reference 28

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source=pdf_text observed=2026-08-03T14:05:26.073897Z digest=sha256:27429f9135312dce12bea4fd8b557b23319a671fccac90bd8ef1919151326c52

Observation 0f9bbdd0-774f-4db2-888e-c2036834bd31 · outbound

This paper cites Deep residual learning for image recognition.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Deep residual learning for image recognition

Reference 29

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source=pdf_text observed=2026-08-03T14:05:26.081342Z digest=sha256:4472ef9b22c045bacbf9fda03487b196ea9dfe39299624f33eb23bcc0e80a214

Observation 405fe2a4-faf7-4c1b-adb7-9dc1b83463b0 · outbound

This paper cites QUEST: Query Stream for Practical Cooperative Perception.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration QUEST: Query Stream for Practical Cooperative Perception

Reference 30

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source=pdf_text observed=2026-08-03T14:05:26.087137Z digest=sha256:0669dbe47f99fcffba810c3714ad0b6b97857290cb745b10fae2cd6c21e4bc98

Observation f323c690-723c-4aef-8456-ed6b8d0b47be · outbound

This paper cites Transiff: An instance-level feature fusion framework for vehicle- infrastructure cooperative 3d detection with transformers.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Transiff: An instance-level feature fusion framework for vehicle- infrastructure cooperative 3d detection with transformers

Reference 31

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source=pdf_text observed=2026-08-03T14:05:26.092782Z digest=sha256:47c1bf5b4ea22b3547ffa83f970b5918f55c87f68eade3b276ae9b405cbc640e

Observation c7428cac-ce28-446c-9077-86e9ad47d8ff · outbound

This paper cites Dense reinforcement learning for safety validation of autonomous vehicles.Nature, 615(7953):620–627, 2023.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Dense reinforcement learning for safety validation of autonomous vehicles.Nature, 615(7953):620–627, 2023

Reference 32

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source=pdf_text observed=2026-08-03T14:05:26.106027Z digest=sha256:c905dff11afe241780c5661793962de87b096b3aac4d82d1f30fef655a11e641

Observation f63335c2-d72d-4a11-b7e4-83d2698b505c · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 33

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source=pdf_text observed=2026-08-03T14:05:26.129241Z digest=sha256:ee65a6c17cb45e910e6a16165576fecd23d54697c9906f8cb75d8b49652f57f6

Pith citing papers

No inbound Pith citation observations are available.