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Paper Citation Record · LEDGER

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software

As of 15 August 2026, this Paper Citation Record lists 100 of 184 outbound references and 0 inbound Pith citation observations for arXiv:2508.20892.

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

pith.paper-citation-record.v1
2508.20892 v1

Coverage vector

measured 100 of 184 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:47:24.519450Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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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Source: cited_works

Reference resolution

100 of 184 outbound references displayed

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  • unresolved95
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Outbound references

Observation 236212a4-0db8-4e36-9afc-277082ca3c52 · outbound

This paper cites Autoware on board: Enabling autonomous vehicles with embedded systems.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Autoware on board: Enabling autonomous vehicles with embedded systems

Reference 1

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Observation 363b6e99-6254-44ee-800b-f8b0f8b05760 · outbound

This paper cites Apollo: Open source autonomous driving plat- form.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Apollo: Open source autonomous driving plat- form

Reference 2

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Observation 15600cf8-20de-4b3e-a2ab-df0e7f27d91d · outbound

This paper cites Planning- oriented autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Planning- oriented autonomous driving

Reference 3

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Observation 724e97d7-6cda-4cf7-a4a1-cc482401e4c9 · outbound

This paper cites LingoQA: Visual Question Answering for Autonomous Driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software LingoQA: Visual Question Answering for Autonomous Driving

Reference 4

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Observation 7a0362ac-61d1-4aae-a8a3-617464623eb4 · outbound

This paper cites Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 5

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Observation 4370484c-0a2d-461c-aa03-c9f2f2e01a07 · outbound

This paper cites Robustness-aware 3d object detection in autonomous driving: A review and outlook.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Robustness-aware 3d object detection in autonomous driving: A review and outlook

Reference 6

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Observation a360c8f9-0ed4-445e-914b-ecde3b0058a3 · outbound

This paper cites Scenario understanding and motion prediction for au- tonomous vehicles—review and comparison.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Scenario understanding and motion prediction for au- tonomous vehicles—review and comparison

Reference 7

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Observation 001e75e7-f9de-4bc8-92d2-ee4ce7f84fa8 · outbound

This paper cites 3D object detection for autonomous driving: A comprehensive survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software 3D object detection for autonomous driving: A comprehensive survey

Reference 8

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Observation c1239dd9-0627-4273-9c99-593fbd81c95d · outbound

This paper cites 3d object detection from images for autonomous driving: a survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software 3d object detection from images for autonomous driving: a survey

Reference 9

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Observation ca3263f0-0ded-4565-ad7c-737b9b05de2c · outbound

This paper cites Echoes beyond points: Unleashing the power of raw radar data in multi- modality fusion.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Echoes beyond points: Unleashing the power of raw radar data in multi- modality fusion

Reference 10

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Observation 189d85d1-c6a8-4d27-9a5f-c649eba15857 · outbound

This paper cites Multi- modal 3d object detection in autonomous driving: A survey and taxonomy.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multi- modal 3d object detection in autonomous driving: A survey and taxonomy

Reference 11

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Observation d14ad2ba-5494-4e73-a03e-145765d3041d · outbound

This paper cites Radar-camera fusion for object detection and semantic segmentation in autonomous driving: A comprehensive review.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Radar-camera fusion for object detection and semantic segmentation in autonomous driving: A comprehensive review

Reference 12

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Observation 51f07275-4140-4561-b509-dc1e6bf3ae2f · outbound

This paper cites A review of lidar- based 3d object detection via deep learning approaches towards robust connected and autonomous vehicles.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A review of lidar- based 3d object detection via deep learning approaches towards robust connected and autonomous vehicles

Reference 13

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Observation aede42fc-c208-47e7-9900-bbb4c53cd0e8 · outbound

This paper cites Multiple object tracking: A literature review.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multiple object tracking: A literature review

Reference 14

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Observation ffd54eac-aa91-4777-84bc-207ffaaae949 · outbound

This paper cites Multiple object tracking in recent times: A literature review.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multiple object tracking in recent times: A literature review

Reference 15

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Observation 338065d7-5056-4b4b-a9f5-b329f5ca3e88 · outbound

This paper cites A system- atic survey on recent deep learning-based approaches to multi-object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A system- atic survey on recent deep learning-based approaches to multi-object tracking

Reference 16

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Observation 92c663b2-4e91-4384-89b8-fdd1946eb900 · outbound

This paper cites Multi-object tracking: a systematic literature review.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multi-object tracking: a systematic literature review

Reference 17

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Observation 4d55317c-fb0f-42aa-b1fb-ba1594664d62 · outbound

This paper cites Data association in multiple object tracking: A survey of recent techniques.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Data association in multiple object tracking: A survey of recent techniques

Reference 18

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Observation 023072d8-7de6-4446-9d6a-e0c5b0a1e90b · outbound

This paper cites A review of tracking and trajectory prediction methods for autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A review of tracking and trajectory prediction methods for autonomous driving

Reference 19

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Observation 8624d12d-a7c5-467c-8e1f-02ddac9cc2ea · outbound

This paper cites A survey on trajectory-prediction methods for autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A survey on trajectory-prediction methods for autonomous driving

Reference 20

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Observation 0e6beeec-c955-44fa-a0ea-0826af9b9f9b · outbound

This paper cites Incorporating driving knowledge in deep learning based vehicle trajectory prediction: A survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Incorporating driving knowledge in deep learning based vehicle trajectory prediction: A survey

Reference 21

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Observation 2ff71263-1596-4ebe-b309-9f6a7a2c4e82 · outbound

This paper cites Machine learning for autonomous vehicle’s trajectory prediction: A comprehensive survey, challenges, and future research directions.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Machine learning for autonomous vehicle’s trajectory prediction: A comprehensive survey, challenges, and future research directions

Reference 22

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Observation 42cbe8b2-d933-4592-8ee4-04e39bdedd51 · outbound

This paper cites A review of deep learning-based vehicle motion prediction for au- tonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A review of deep learning-based vehicle motion prediction for au- tonomous driving

Reference 23

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Observation 87ad6495-a00c-4e8c-b836-9ebea31c77cd · outbound

This paper cites Evaluating pedestrian trajectory prediction methods with respect to autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Evaluating pedestrian trajectory prediction methods with respect to autonomous driving

Reference 24

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Observation d6edd7aa-24fa-4470-ae15-72004cccf2b7 · outbound

This paper cites Vision meets robotics: The kitti dataset.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Vision meets robotics: The kitti dataset

Reference 25

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Observation d959034c-558e-47ba-8dfc-bd2a458938b0 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software nuscenes: A multimodal dataset for autonomous driving

Reference 26

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Observation f0ef7be8-fba7-4d7f-a1ba-23546da0f77a · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Scalability in perception for autonomous driving: Waymo open dataset

Reference 27

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Observation f84ed580-7045-4075-b2db-2b9c5fbe2043 · outbound

This paper cites Recent advancements in end-to-end autonomous driving using deep learning: A survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Recent advancements in end-to-end autonomous driving using deep learning: A survey

Reference 28

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Observation ccf3e4f8-36d8-4460-8c90-65f986c9290e · outbound

This paper cites A survey of end-to-end driving: Architectures and training methods.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A survey of end-to-end driving: Architectures and training methods

Reference 29

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Observation 25fab7c5-3aca-4307-a17f-d1e2381b737e · outbound

This paper cites End-to-end Autonomous Driving using Deep Learning: A Systematic Review.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software End-to-end Autonomous Driving using Deep Learning: A Systematic Review

Reference 30

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Observation 3bb72785-137f-4ad3-b2cc-5154651b4423 · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software End-to-end autonomous driving: Challenges and frontiers

Reference 31

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Observation 88eeb4b2-4bb7-4a50-80f5-6c3a38c37df6 · outbound

This paper cites End-to-End Autonomous Driving in CARLA: A Survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software End-to-End Autonomous Driving in CARLA: A Survey

Reference 32

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Observation 8a120fc3-7e5f-4a5e-b23e-eeec2972d1ea · outbound

This paper cites Joint Perception and Prediction for Autonomous Driving: A Survey.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Joint Perception and Prediction for Autonomous Driving: A Survey

Reference 33

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Observation 3a248231-feb9-4369-b9d1-92160bf3fd6c · outbound

This paper cites Memot: Multi-object tracking with memory.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Memot: Multi-object tracking with memory

Reference 34

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Observation bf83ab4f-4a25-4903-9ffb-b9458d77efa0 · outbound

This paper cites Tracking objects as points.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Tracking objects as points

Reference 35

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Observation e2bf9844-aeaf-412e-b191-af09b9b82fa2 · outbound

This paper cites Objects as Points.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Objects as Points

Reference 36

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Observation ee79f457-74b0-4524-ba6b-24c2dada9aa1 · outbound

This paper cites Tubetk: Adopting tubes to track multi-object in a one-step training model.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Tubetk: Adopting tubes to track multi-object in a one-step training model

Reference 37

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Observation 066c4f7f-6c7b-4986-94f0-5ddbbaaba797 · outbound

This paper cites Can spatiotempo- ral 3d cnns retrace the history of 2d cnns and imagenet? In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition , pages 6546–6555, 2018.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Can spatiotempo- ral 3d cnns retrace the history of 2d cnns and imagenet? In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition , pages 6546–6555, 2018

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Observation 0e35c665-cd13-4ef2-a6ba-1ad14761394d · outbound

This paper cites Learn- ing to track with object permanence.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Learn- ing to track with object permanence

Reference 39

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Observation 5dd84497-3d52-49a6-8e75-57bbe2d39a55 · outbound

This paper cites Tracking objects as pixel-wise distributions.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Tracking objects as pixel-wise distributions

Reference 40

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Observation 2354e852-1985-4b72-bdc1-fdf547eadc46 · outbound

This paper cites Deep residual learning for image recognition.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Deep residual learning for image recognition

Reference 41

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source=pdf_text observed=2026-08-05T14:47:24.010217Z digest=sha256:4f5c9f9cbd82d27b284b98d29b2ac1d90d96d601964d76a94d3655bee96e9be6

Observation 7cd45420-0ed0-469e-b275-5fb554eb4b0a · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 42

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source=pdf_text observed=2026-08-05T14:47:24.017288Z digest=sha256:c7da04375421ab0d8a1c81e014733fec77ab8178b5e8018f2d37bc859bb568fa

Observation 60f31d61-7f34-4faa-b210-6c85af611118 · outbound

This paper cites Flow- guided feature aggregation for video object detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Flow- guided feature aggregation for video object detection

Reference 43

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source=pdf_text observed=2026-08-05T14:47:24.024928Z digest=sha256:6355862443dc9dd5619816fd95db8e1acef96e25e267f254954f02d13e4e0833

Observation d61983d4-f207-4fa3-a9e2-ec5ea3e26288 · outbound

This paper cites Monocular quasi-dense 3d object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Monocular quasi-dense 3d object tracking

Reference 44

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source=pdf_text observed=2026-08-05T14:47:24.033587Z digest=sha256:a9a27b14cd53bcbc63e0571d9e0026640802e4cc3f94544c7e3f991a762a5961

Observation 07402114-091e-448d-b3c1-531fde543c02 · outbound

This paper cites Faster r- cnn: Towards real-time object detection with region proposal networks.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Faster r- cnn: Towards real-time object detection with region proposal networks

Reference 45

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source=pdf_text observed=2026-08-05T14:47:24.043060Z digest=sha256:cc622dd5a21f36a084a42d4b25ce5d1057321c96da57e059f86c257eac60514d

Observation 2319b6bd-02e0-4a17-bc83-4bc9c8f490ce · outbound

This paper cites Star-track: Latent motion models for end-to-end 3d object tracking with adaptive spatio-temporal appearance representations.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Star-track: Latent motion models for end-to-end 3d object tracking with adaptive spatio-temporal appearance representations

Reference 46

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source=pdf_text observed=2026-08-05T14:47:24.050119Z digest=sha256:109dc8e55b83680db9fc0003a7b9eb39ab50c1026cb39d6103bcc2edb5784012

Observation aa60ba3c-8f22-44ab-b281-c110d8f9b583 · outbound

This paper cites Detr3d: 3d object detection from 17 multi-view images via 3d-to-2d queries.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Detr3d: 3d object detection from 17 multi-view images via 3d-to-2d queries

Reference 47

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source=pdf_text observed=2026-08-05T14:47:24.057419Z digest=sha256:581f78b153aa00faa7eae964c004b49dc0e23b335e2d3197e949d89bdca82904

Observation b538d47b-56d2-496f-84f7-667b3e737726 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Center-based 3d object detection and tracking

Reference 48

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source=pdf_text observed=2026-08-05T14:47:24.065089Z digest=sha256:d9986d6dd1bd242ddd1d2fbe904c75f07a3eb879c0829a0d12842bf55cab7fdc

Observation 60f28601-732b-47a4-b2f5-81672c1f1271 · outbound

This paper cites V oxelnet: End-to-end learning for point cloud based 3d object detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software V oxelnet: End-to-end learning for point cloud based 3d object detection

Reference 49

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source=pdf_text observed=2026-08-05T14:47:24.072456Z digest=sha256:1396653f25295690a81d44f81a1032ad94fb3920242726ebb7326dad188cc975

Observation 2f88508f-71a0-4985-949a-cee39df6d456 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Pointpillars: Fast encoders for object detection from point clouds

Reference 50

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source=pdf_text observed=2026-08-05T14:47:24.079912Z digest=sha256:cd6b6d81142af9f7b4ce436893b35941c1055742a8dc27f24ec2753a2c8c3dce

Observation ad49089b-29aa-4657-a3a9-a528a5577eed · outbound

This paper cites Exploring simple 3d multi-object tracking for autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Exploring simple 3d multi-object tracking for autonomous driving

Reference 51

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source=pdf_text observed=2026-08-05T14:47:24.087143Z digest=sha256:7e5348652f5181d38d917176426da09094c462737ec978ff65c9b812f5a5facb

Observation 241842eb-14d3-4470-a0ad-e88ec4533e1e · outbound

This paper cites CenterTube: Tracking multiple 3D objects with 4D tubelets in dynamic point clouds.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software CenterTube: Tracking multiple 3D objects with 4D tubelets in dynamic point clouds

Reference 52

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source=pdf_text observed=2026-08-05T14:47:24.100907Z digest=sha256:fea876f51d03a86d97d389e6c6194a3dff4592e5368c6c3c50ed66cc8291b98a

Observation a47c709c-0aed-4267-b5e4-423180b64da4 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software V oxelnext: Fully sparse voxelnet for 3d object detection and tracking

Reference 53

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source=pdf_text observed=2026-08-05T14:47:24.110714Z digest=sha256:f7f97abc84ca74c52f2711ab7824cd7694946be0549e1b1f49ea60378de90fcc

Observation f259267b-6ed5-4005-b05e-6e44c01108b2 · outbound

This paper cites A Multi- Modal Fusion-Based 3D Multi-Object Tracking Framework with Joint Detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software A Multi- Modal Fusion-Based 3D Multi-Object Tracking Framework with Joint Detection

Reference 54

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source=pdf_text observed=2026-08-05T14:47:24.120326Z digest=sha256:8f04f49aaf70d93c717373177034427465fa320a7f229a4451c70ffc7587acd0

Observation 6b477757-fa7f-4207-b694-7cdfa46fa9a6 · outbound

This paper cites Towards real-time multi-object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Towards real-time multi-object tracking

Reference 55

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source=pdf_text observed=2026-08-05T14:47:24.128794Z digest=sha256:9fad7901587ff6ddd94f08ae0c978dafba5301097f19b3ccf3f11e7b617e538e

Observation 20833841-05e9-4d56-82a3-a050b0d65656 · outbound

This paper cites YOLOv3: An Incremental Improvement.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software YOLOv3: An Incremental Improvement

Reference 56

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source=pdf_text observed=2026-08-05T14:47:24.134724Z digest=sha256:b0bab4d2dac25d89c40f5b23638f59aee41dddd56f263332192f29ade4140c63

Observation cffc0ade-d671-46c2-a01c-289787d54d08 · outbound

This paper cites Retina- track: Online single stage joint detection and tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Retina- track: Online single stage joint detection and tracking

Reference 57

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source=pdf_text observed=2026-08-05T14:47:24.147652Z digest=sha256:c237b2716ce84f1c9419176ca69cdffc4ae239a0be8373d3c4321bb9aaeebb68

Observation 99bb39d6-8bb2-46bd-8e33-40a558a7bef9 · outbound

This paper cites Multi-Object Tracking with Siamese Track-RCNN.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multi-Object Tracking with Siamese Track-RCNN

Reference 58

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source=pdf_text observed=2026-08-05T14:47:24.157791Z digest=sha256:126799fa25d733ed8eab23ee250775ffac8ab183fdd87836564289c7c660b261

Observation 3beacb95-8e34-46b3-8868-c3538e2627c6 · outbound

This paper cites Chained-tracker: Chaining paired attentive regression results for end-to- end joint multiple-object detection and tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Chained-tracker: Chaining paired attentive regression results for end-to- end joint multiple-object detection and tracking

Reference 59

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source=pdf_text observed=2026-08-05T14:47:24.173552Z digest=sha256:dbc3a39959574c4aac14fa3406291b5e88c10c9d03b2102d28a3a725e4440488

Observation be891e78-3cfe-450b-97d6-b132d6d0925d · outbound

This paper cites DEFT: Detection Embeddings for Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software DEFT: Detection Embeddings for Tracking

Reference 60

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source=pdf_text observed=2026-08-05T14:47:24.186359Z digest=sha256:c3991ede25d5c54ef88524c9273b63a956049c0136f633eec8d953a9fa54c778

Observation 579f4163-3e7a-4f80-ad9a-807c996794a5 · outbound

This paper cites Fairmot: On the fairness of detection and re-identification in multiple object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Fairmot: On the fairness of detection and re-identification in multiple object tracking

Reference 61

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source=pdf_text observed=2026-08-05T14:47:24.192033Z digest=sha256:98ea802d3e8368311c136d36b1fba5d3aee97b00ce973be3ef12283d336857ca

Observation 56e83950-33f8-487f-ad5c-6c067e88d639 · outbound

This paper cites Joint object detection and multi-object tracking with graph neural networks.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Joint object detection and multi-object tracking with graph neural networks

Reference 62

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source=pdf_text observed=2026-08-05T14:47:24.199194Z digest=sha256:5caaa7031a950c26fc5e9b6535e23b822067e37dc98a7e5dbe6a43a86aa151da

Observation c2ba4bac-123d-432d-a5cd-b7ec7aaefe16 · outbound

This paper cites Multiple object tracking with correlation learning.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multiple object tracking with correlation learning

Reference 63

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source=pdf_text observed=2026-08-05T14:47:24.211067Z digest=sha256:b69a751c4189877b0b006a770ca49e33ac899387ea9963bc7e43234d98d9c61f

Observation 3a0b3b93-e89b-4f4e-b957-f4a1fe1523df · outbound

This paper cites Anchor-free person search.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Anchor-free person search

Reference 64

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source=pdf_text observed=2026-08-05T14:47:24.219806Z digest=sha256:23caf978cc2f3ba77ccbf1ded0fdb75667b953a77233cfdc683b0294a5994781

Observation 7cbeaa35-aec6-477d-9633-7bed21fe9520 · outbound

This paper cites Fcos: Fully convo- lutional one-stage object detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Fcos: Fully convo- lutional one-stage object detection

Reference 65

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source=pdf_text observed=2026-08-05T14:47:24.227094Z digest=sha256:3a43b0ded4882f5979d9aefecad443eaba365fb87e6805363cac1840740fe8f0

Observation 2fc9a7df-628a-4ea2-bef0-ac6ea78b6c41 · outbound

This paper cites Time3d: End-to-end joint monocular 3d object detection and tracking for autonomous driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Time3d: End-to-end joint monocular 3d object detection and tracking for autonomous driving

Reference 66

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source=pdf_text observed=2026-08-05T14:47:24.233954Z digest=sha256:e3131eb7c2586878027dc4574370a04045348168e3d4be3002d840d5db479e8c

Observation 707a3512-4c19-4aba-8e54-de8210c85c4f · outbound

This paper cites Monocular 3d detection with geometric constraint embedding and semi-supervised training.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Monocular 3d detection with geometric constraint embedding and semi-supervised training

Reference 67

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source=pdf_text observed=2026-08-05T14:47:24.243689Z digest=sha256:702722114dbcde08eb44a98735c1aeff63a0dd90afc59e7770a8f90a49a6bd64

Observation a6c40e5e-b3cf-48ae-a53d-0cb5606fbc7e · outbound

This paper cites Track to detect and segment: An online multi-object tracker.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Track to detect and segment: An online multi-object tracker

Reference 68

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source=pdf_text observed=2026-08-05T14:47:24.252367Z digest=sha256:64e9fd29e8e1f06d0dd9748f2bcd246ca367d7aa6ba7056df5d8dc60697037aa

Observation 61284ee1-e04c-4767-8d34-7c2878291dae · outbound

This paper cites Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking

Reference 69

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source=pdf_text observed=2026-08-05T14:47:24.258347Z digest=sha256:1c3adb5a572934d4edf335054827a4865b0f06ecdb92091ab5ece5495d4a23a5

Observation b5d0fbc6-7844-4974-ab9a-574308c58ca7 · outbound

This paper cites Second: Sparsely embedded convolutional detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Second: Sparsely embedded convolutional detection

Reference 70

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source=pdf_text observed=2026-08-05T14:47:24.264757Z digest=sha256:d20b28949b26d99631bf2c9d2d40b916239771f70362bf98275f1753da052bc5

Observation 399858a6-caf7-472c-903b-579293176b19 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Joint multi-object detection and tracking with camera-LiDAR fusion for autonomous driving

Reference 71

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source=pdf_text observed=2026-08-05T14:47:24.270011Z digest=sha256:30fa85e8a0b27242c97c1ce6ba45e0f67b04e87f69fd69d781c9f9e8e404db65

Observation 39d6281b-c93d-421e-aff5-dbed404899b9 · outbound

This paper cites Cross-modal 3d object detection and tracking for auto-driving.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Cross-modal 3d object detection and tracking for auto-driving

Reference 72

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source=pdf_text observed=2026-08-05T14:47:24.276453Z digest=sha256:e5b2df6cafb5f160ce56fd3c72a985cb4964e01ea2866da8abee31fc45bdaa02

Observation 6757c058-2b57-49ad-81bd-60ab4622ba56 · outbound

This paper cites Joint 3d object detection and tracking using spatio-temporal representation of camera image and lidar point clouds.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Joint 3d object detection and tracking using spatio-temporal representation of camera image and lidar point clouds

Reference 73

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source=pdf_text observed=2026-08-05T14:47:24.282312Z digest=sha256:882ee2244c0f44a519edfa6a6715f87e02416e24eba560d68c99a7fe88edf0fe

Observation 320c4a0c-cfd1-4136-8180-88b19edc928a · outbound

This paper cites 3d- cvf: Generating joint camera and lidar features using cross-view spatial feature fusion for 3d object detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software 3d- cvf: Generating joint camera and lidar features using cross-view spatial feature fusion for 3d object detection

Reference 74

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source=pdf_text observed=2026-08-05T14:47:24.290621Z digest=sha256:6e80dadf773c94d5259fad786ed1f67e98edcae8ec9e2f29a4778eda8e3e6741

Observation 679499e7-9a53-4ac6-995f-4b4769f058b5 · outbound

This paper cites TransTrack: Multiple Object Tracking with Transformer.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software TransTrack: Multiple Object Tracking with Transformer

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source=pdf_text observed=2026-08-05T14:47:24.296123Z digest=sha256:8e46a8cc6a9fe27e18b0a88c21c02781238638a5a123078baf2f4d0c4d94b629

Observation 720d59e9-f312-422c-9a26-7a0985902726 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Trackformer: Multi-object tracking with transformers

Reference 76

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source=pdf_text observed=2026-08-05T14:47:24.305824Z digest=sha256:f8b444b9ba446fda644333256830814a06a0a5f03361027def9e77b08dff82a6

Observation 1ddd97a6-d33a-49a6-be3b-77fec474cd33 · outbound

This paper cites TransCenter: Transformers with dense representations for multiple-object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software TransCenter: Transformers with dense representations for multiple-object tracking

Reference 77

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source=pdf_text observed=2026-08-05T14:47:24.311171Z digest=sha256:f441427fe228db38fbebd7da6c47a50e7bb1011c59ffe7aa8b355fef481940fa

Observation 1ed8c668-b75e-451d-93da-3e2666538278 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software End-to-end object detection with transformers

Reference 78

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source=pdf_text observed=2026-08-05T14:47:24.317791Z digest=sha256:04c94b9161d3e69c638ac63fe861f074c04fc6dcf40c8162a3e548390f97b21c

Observation 8eab826b-ecea-42b1-acd5-333c17ffc49b · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Pvt v2: Improved baselines with pyramid vision transformer

Reference 79

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source=pdf_text observed=2026-08-05T14:47:24.324416Z digest=sha256:dd342d593a121de727f3cadcf83c7c4c79f0c4a83b92839573b7b9d5950cc29b

Observation f69a9bc9-1ccf-4fb9-bb8c-3ca44b77a620 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Motr: End-to-end multiple-object tracking with transformer

Reference 80

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source=pdf_text observed=2026-08-05T14:47:24.331133Z digest=sha256:0db223a21def5451163affa491260562cbfe6cc306cbe9424fdae9e3991ea133

Observation 2cddff11-482f-4787-8151-39a9fd1c967f · outbound

This paper cites Motrv2: Bootstrap- ping end-to-end multi-object tracking by pretrained object detectors.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Motrv2: Bootstrap- ping end-to-end multi-object tracking by pretrained object detectors

Reference 81

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source=pdf_text observed=2026-08-05T14:47:24.342290Z digest=sha256:6e45af51a1b97edeed9b8af982e8018d9381e433224974447c2dfda5ac10b308

Observation 7bc4905f-00ea-4157-b2da-d45d3dc2edea · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software YOLOX: Exceeding YOLO Series in 2021

Reference 82

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.355412Z digest=sha256:bf7aab33897cc6e203d82d990521de7468ddbc31b3bfec84286ac538714c95df

Observation e95bf644-a711-4fc9-8d56-3e5cb4a4bf35 · outbound

This paper cites MOTRv3: Release-Fetch Supervision for End-to-End Multi-Object Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software MOTRv3: Release-Fetch Supervision for End-to-End Multi-Object Tracking

Reference 83

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.364018Z digest=sha256:be33504181e7abfdd256d70e9171ac8dc27751b099b6462865a4c60db96a25f7

Observation 5b04a137-eba9-431e-8b57-6ffa944c3518 · outbound

This paper cites Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking

Reference 84

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.373284Z digest=sha256:1c410c3796dfc3c0a4a91aa4b4381cf15750794a6d6c9c64041fbd1fe4895599

Observation 8e816333-9ac3-4d44-a819-7d1008706d29 · outbound

This paper cites MeMOTR: Long-term memory- augmented transformer for multi-object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software MeMOTR: Long-term memory- augmented transformer for multi-object tracking

Reference 85

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.383430Z digest=sha256:9914a29851a6e4b1355ac0c3c568aef13fb04074724bc4f392e58634ea856d3c

Observation 7b577418-2ba7-4b3d-b9a9-634b34a4eece · outbound

This paper cites Multi- object Tracking by Detection and Query: an efficient end-to-end manner.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Multi- object Tracking by Detection and Query: an efficient end-to-end manner

Reference 86

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T14:47:24.390110Z digest=sha256:7b15b48a5b856e44ab78dd9ae4ecd55a177d5dc76ab8cff11e54b7d05e074c4f

Observation b98bec31-4505-4416-b54c-b799f79468e0 · outbound

This paper cites Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking

Reference 87

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.398907Z digest=sha256:87464edcd160a4d76fd8fb0ba13e8e2d7e10e96d9a633be1f6727ea8da73a9ef

Observation 6e79fde7-c527-49db-9128-cb834146e3b5 · outbound

This paper cites Mutr3d: A multi-camera tracking framework via 3d-to-2d queries.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Mutr3d: A multi-camera tracking framework via 3d-to-2d queries

Reference 88

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source=pdf_text observed=2026-08-05T14:47:24.404896Z digest=sha256:7225f3884c7d00883bab672be987e8d0e3c775b77cf2a64b8d781bb29e7a8300

Observation 9e32463f-180d-4c0f-b5c3-7ae3e24f7827 · outbound

This paper cites End-to-end 3d tracking with 18 decoupled queries.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software End-to-end 3d tracking with 18 decoupled queries

Reference 89

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source=pdf_text observed=2026-08-05T14:47:24.411225Z digest=sha256:2548c71b4df3fb9bda5c6f998922430cc1fad774f1038dfe113452ec0bb62244

Observation e81e739d-8645-41d7-9d79-e05006570279 · outbound

This paper cites Ada-track: End-to-end multi-camera 3d multi-object tracking with alternating detection and association.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Ada-track: End-to-end multi-camera 3d multi-object tracking with alternating detection and association

Reference 90

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source=pdf_text observed=2026-08-05T14:47:24.420040Z digest=sha256:7a917de38aca55fac31147febc68d5f72d8e3d3861fcac58c8166a0f1e17d0c2

Observation b1b61c15-57fc-4e56-a547-2ddefe7a437a · outbound

This paper cites OneTrack: Demystifying the Conflict Between Detection and Tracking in End-to- End 3D Trackers.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software OneTrack: Demystifying the Conflict Between Detection and Tracking in End-to- End 3D Trackers

Reference 91

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source=pdf_text observed=2026-08-05T14:47:24.427496Z digest=sha256:b0a85ccdec10d167c4d0ce7e3732275a44db8998dba3fcd463f9482c3b879df5

Observation c9b4d79a-5e82-4a39-924c-a3a8be3b9f5e · outbound

This paper cites Exploring object-centric temporal modeling for efficient multi-view 3d object detection.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Exploring object-centric temporal modeling for efficient multi-view 3d object detection

Reference 92

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source=pdf_text observed=2026-08-05T14:47:24.461638Z digest=sha256:eb724957c52c65194d777801ab2d63f1b511eb3d8e463bcfd86fe3c3adf23f84

Observation 8a0b1e66-adfe-40ae-8556-13837ddaee78 · outbound

This paper cites MCTR: Multi Camera Tracking Transformer.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software MCTR: Multi Camera Tracking Transformer

Reference 93

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source=pdf_text observed=2026-08-05T14:47:24.469813Z digest=sha256:27441db1a1ccfd68c20c762af0736493955a57ab8e849e616c4420c904e094d3

Observation d846ea28-0553-4d09-b903-5cca99b5fcca · outbound

This paper cites JDT3D: Address- ing the Gaps in LiDAR-Based Tracking-by-Attention.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software JDT3D: Address- ing the Gaps in LiDAR-Based Tracking-by-Attention

Reference 94

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.476315Z digest=sha256:5c1b1f13bc7d7b463806461f66ff6ba11c5f0fd2a99f7eccd6a3282457b490c4

Observation 1177737d-105b-45e6-b858-b2c7ec9bb0da · outbound

This paper cites Mask4former: Mask transformer for 4d panoptic segmentation.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Mask4former: Mask transformer for 4d panoptic segmentation

Reference 95

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.484235Z digest=sha256:3c1d73e2809d802db6ca158be532cc7a152353bbec4f283c81d011e52fd7f467

Observation 2018f266-6f97-4e11-8aa3-2908ac57e65e · outbound

This paper cites Motiontrack: Learning robust short-term and long-term motions for multi-object tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Motiontrack: Learning robust short-term and long-term motions for multi-object tracking

Reference 96

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.490078Z digest=sha256:4e3f7ddf3e2ca30c4e0d5343a4408568b101164c41860c8564f4386045e0058c

Observation 0b90310a-c6ee-4103-8214-1d8d1046e09f · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Transfusion: Robust lidar-camera fusion for 3d object detection with transformers

Reference 97

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.497386Z digest=sha256:21c95aebde216f7dba297b9e8ee2c6f89d8f17cc5337fd1d8353aa007b8ea2ca

Observation 73014362-d50d-466d-b40f-b1bd62e08693 · outbound

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

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software Argoverse 2: Next Generation Datasets for Self-driving Perception and Forecasting

Reference 98

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.503900Z digest=sha256:8c7530c05d2434f4f56e73c9fa114d7cb19f69bdab217e60fdd4dc0a8b73b5dc

Observation 304ac416-75d8-4d8b-bcd6-ebf4379d8617 · outbound

This paper cites MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking

Reference 99

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.512799Z digest=sha256:cd9679d02969081be4a31a7b3b9a31e9ce41688c58147a78a0aacbb349d345f9

Observation 531615f8-d38f-496e-bb20-d8655e99d8e2 · outbound

This paper cites MOT16: A Benchmark for Multi-Object Tracking.

To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software MOT16: A Benchmark for Multi-Object Tracking

Reference 100

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:47:24.519450Z digest=sha256:71282ed6057f8463dfd5f031a86983943554f5c22f77a183db330bd589e64e16

Pith citing papers

No inbound Pith citation observations are available.