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Paper Citation Record · LEDGER

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2411.08433.

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

pith.paper-citation-record.v1
2411.08433 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:40:26.060155Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T06:02:33.241748Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T06:54:20.975418Z

Reference resolution

31 of 31 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f59bb327-9f4e-47ec-8966-32bc5de596f1 · outbound

This paper cites 3d multi-object tracking: A baseline and new evaluation metrics,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter 3d multi-object tracking: A baseline and new evaluation metrics,

Reference 1

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Observation 051df9d9-3fca-4e50-ba53-968837ff0482 · outbound

This paper cites Center-based 3d object detec- tion and tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Center-based 3d object detec- tion and tracking,

Reference 2

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Observation 202b80ce-3a05-4847-b3b8-fd1263e440fc · outbound

This paper cites You only look once: Unified, real-time object detection,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter You only look once: Unified, real-time object detection,

Reference 3

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Observation 67b95e50-d6dc-4407-aba5-709771e1c7a9 · outbound

This paper cites End-to-end object detection with transformers,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter End-to-end object detection with transformers,

Reference 4

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Observation 22b41fd8-d03a-43ae-89d1-829446916608 · outbound

This paper cites V oxelnext: Fully sparse voxelnet for 3d object detection and tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter V oxelnext: Fully sparse voxelnet for 3d object detection and tracking,

Reference 5

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Observation 01347560-53ba-410d-94f0-a7b1047b75b9 · outbound

This paper cites Simpletrack: Understanding and rethinking 3d multi-object tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Simpletrack: Understanding and rethinking 3d multi-object tracking,

Reference 6

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Observation f3023c27-7c1a-47d9-b22d-2172031dc461 · outbound

This paper cites Poly-mot: A polyhedral framework for 3d multi-object tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Poly-mot: A polyhedral framework for 3d multi-object tracking,

Reference 7

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Observation ae31ad7e-5b02-4e69-86d5-cb775c09ee34 · outbound

This paper cites Joint multi-object detection and tracking with camera-lidar fusion for autonomous driving,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Joint multi-object detection and tracking with camera-lidar fusion for autonomous driving,

Reference 8

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Observation 840277bf-aaab-4bcd-b780-f0b92605eca1 · outbound

This paper cites Learnable online graph representations for 3d multi-object tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Learnable online graph representations for 3d multi-object tracking,

Reference 9

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Observation ccd55728-9760-4759-9848-7d899fcbafcb · outbound

This paper cites Eagermot: 3d multi-object tracking via sensor fusion,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Eagermot: 3d multi-object tracking via sensor fusion,

Reference 10

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Observation 065c0c0d-4460-4bd9-9154-4fcd307f2e2f · outbound

This paper cites Camo-mot: Combined appearance-motion optimization for 3d multi-object tracking with camera-lidar fusion,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Camo-mot: Combined appearance-motion optimization for 3d multi-object tracking with camera-lidar fusion,

Reference 11

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Observation c0eb1109-3a6e-4905-885b-379123a406d7 · outbound

This paper cites A new approach to linear filtering and prediction problems,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter A new approach to linear filtering and prediction problems,

Reference 12

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Observation 8d18ebfa-71e4-4a1d-a637-e62a6959a8f2 · outbound

This paper cites Gruber, AN APPROACH TO TARGET TRACKING.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Gruber, AN APPROACH TO TARGET TRACKING

Reference 13

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Observation 29a8a63b-173c-4d60-ab48-c38e3fffb62e · outbound

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3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Unresolved cited work

Reference 14

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Observation d1ec4312-c7ba-454a-b40c-61ca623a30d8 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 15

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Observation dabbc5a2-50f0-4b74-ab2e-0be374e7e500 · outbound

This paper cites Long short-term memory,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Long short-term memory,

Reference 16

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Observation 2b0ac8c7-9ad9-44be-bc80-46a09572d431 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter nuscenes: A multimodal dataset for autonomous driving,

Reference 17

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Observation c047b8b0-21f0-40b1-96d2-92a9e1bf96b0 · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 18

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Observation ecdfd6ab-3fb3-4596-9cca-ff4151f963f8 · outbound

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

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Motiontrack: end-to-end transformer-based multi-object tracking with lidar-camera fusion,

Reference 19

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Observation 3fe778cc-6e70-47c2-85d3-b65752df29da · outbound

This paper cites Attention is all you need,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Attention is all you need,

Reference 20

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Observation a8de676a-cb5b-436d-8cc9-2887ddd8f84e · outbound

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

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,

Reference 21

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Observation e1592a05-d47f-410d-a91f-0c3c7bc5c6b0 · outbound

This paper cites Learning a neural solver for multiple object tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Learning a neural solver for multiple object tracking,

Reference 22

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Observation 09c773af-8c3a-4c33-ad95-3971e4043f91 · outbound

This paper cites Kfnet: Learning temporal camera relocalization using kalman filtering,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Kfnet: Learning temporal camera relocalization using kalman filtering,

Reference 23

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Observation cae44725-353f-4d3f-83d0-349cfc433645 · outbound

This paper cites Combining generative and discriminative models for hybrid inference,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Combining generative and discriminative models for hybrid inference,

Reference 24

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Observation 96ef4a4b-f7aa-4ab3-aaae-06257e6276c1 · outbound

This paper cites Kalmannet: Neural network aided kalman filtering for partially known dynamics,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Kalmannet: Neural network aided kalman filtering for partially known dynamics,

Reference 25

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Observation 711b138d-aea8-4adb-bf2f-6fe19e0bf057 · outbound

This paper cites Score refinement for confidence-based 3d multi-object tracking,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Score refinement for confidence-based 3d multi-object tracking,

Reference 26

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Observation 48b1d267-59be-41c4-bca7-30cdaf9a44dd · outbound

This paper cites Tracking objects as points,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Tracking objects as points,

Reference 27

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Observation ab641a73-98eb-46d9-bbcd-e1e4f4d0db67 · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Cascade r-cnn: Delving into high quality object detection,

Reference 28

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Observation 3db4ae0e-19e5-49fd-9cdd-a7f48b5d564e · outbound

This paper cites LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs

Reference 29

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Observation 80afcf73-4821-4eb8-989e-28f25cf11121 · outbound

This paper cites Towards long-tailed 3d detection,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Towards long-tailed 3d detection,

Reference 30

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Source-reported events for the cited work

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Observation c1101bd0-c738-4654-8433-17dc39c47d64 · outbound

This paper cites Argoverse: 3d tracking and forecasting with rich maps,.

3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter Argoverse: 3d tracking and forecasting with rich maps,

Reference 31

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Pith citing papers

Observation fca3d1fc-e8f8-4b49-a41c-02b096ad6051 · inbound

Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry cites this paper.

Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry 3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter

Reference 34

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Observation 3c3370d9-ee4b-40ef-a4f2-b53f80d4b7ce · inbound

PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking cites this paper.

PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking 3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter

Reference 52

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