Paper Citation Record · LEDGER

2.5D Object Detection for Intelligent Roadside Infrastructure

As of 23 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2507.03564.

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

pith.paper-citation-record.v1
2507.03564 v2

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:12:43.970107Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T21:58:42.295581Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T14:21:07.265246Z

Reference resolution

48 of 48 outbound references displayed

verified exact0
verified fuzzy44
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 821ffb08-c166-49ef-bb55-6444b1500e01 · outbound

This paper cites Predictive Trajec- tory Planning in Situations with Hidden Road Users Using Partially Observable Markov Decision Processes,.

2.5D Object Detection for Intelligent Roadside Infrastructure Predictive Trajec- tory Planning in Situations with Hidden Road Users Using Partially Observable Markov Decision Processes,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.699564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2855d013-2483-458e-a586-6939e1af164f · outbound

This paper cites DigiT4TAF–Bridging Physical and Digital Worlds for Future Trans- portation Systems,.

2.5D Object Detection for Intelligent Roadside Infrastructure DigiT4TAF–Bridging Physical and Digital Worlds for Future Trans- portation Systems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.684370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d7531165-3e54-41f1-83f0-fd437d8096e1 · outbound

This paper cites A Unified Description of Proving Grounds and Test Areas for Automated and Connected Vehicles,.

2.5D Object Detection for Intelligent Roadside Infrastructure A Unified Description of Proving Grounds and Test Areas for Automated and Connected Vehicles,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.670093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b97c2179-99b1-4860-8c81-d5842ca96e41 · outbound

This paper cites TUMTraf V2X Cooperative Perception Dataset,.

2.5D Object Detection for Intelligent Roadside Infrastructure TUMTraf V2X Cooperative Perception Dataset,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.655283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 66ccaac0-19a1-468a-9a47-e9260dc45da4 · outbound

This paper cites Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite,.

2.5D Object Detection for Intelligent Roadside Infrastructure Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T20:12:43.788120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 538d9db3-28bb-481a-9b9e-5919bdc1facb · outbound

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

2.5D Object Detection for Intelligent Roadside Infrastructure nuScenes: A multimodal dataset for autonomous driving,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.630912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 22516de8-2a29-499d-a0b6-a6071a7b4a5e · outbound

This paper cites Scalability in Perception for Autonomous Driving: Waymo Open Dataset,.

2.5D Object Detection for Intelligent Roadside Infrastructure Scalability in Perception for Autonomous Driving: Waymo Open Dataset,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.615553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 159cbcce-b9c1-4edf-9f5b-5d24a612fd53 · outbound

This paper cites Towards Large Scale Urban Traffic Reference Data: Smart Infrastructure in the Test Area Autonomous Driving Baden-W¨urttemberg,.

2.5D Object Detection for Intelligent Roadside Infrastructure Towards Large Scale Urban Traffic Reference Data: Smart Infrastructure in the Test Area Autonomous Driving Baden-W¨urttemberg,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.599280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e4661514-bcf8-44ee-a070-67b12360cb10 · outbound

This paper cites Large-scale ex- traction of accurate vehicle trajectories for driving behavior learning,.

2.5D Object Detection for Intelligent Roadside Infrastructure Large-scale ex- traction of accurate vehicle trajectories for driving behavior learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.582686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4ae40166-e151-4910-8aee-b4a3c351d5e0 · outbound

This paper cites Kalman filtering aspects in camera and deep learning based tracking for traffic monitoring,.

2.5D Object Detection for Intelligent Roadside Infrastructure Kalman filtering aspects in camera and deep learning based tracking for traffic monitoring,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.564741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fbc7ed14-eee9-435d-b476-5e7cf7a36915 · outbound

This paper cites 3D-Net: Monocular 3D object recognition for traffic monitoring,.

2.5D Object Detection for Intelligent Roadside Infrastructure 3D-Net: Monocular 3D object recognition for traffic monitoring,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.548996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1678ff41-6bf6-4960-a6c7-e8869852204e · outbound

This paper cites UrbanNet: Leveraging Urban Maps for Long Range 3D Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure UrbanNet: Leveraging Urban Maps for Long Range 3D Object Detection,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.534278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4dd86c48-4e82-45e8-956f-c5c9a73279a2 · outbound

This paper cites Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography,.

2.5D Object Detection for Intelligent Roadside Infrastructure Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.518209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 81d9ebd0-34b5-4992-af17-056278a76d68 · outbound

This paper cites FCOS3D: Fully Convolu- tional One-Stage Monocular 3D Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure FCOS3D: Fully Convolu- tional One-Stage Monocular 3D Object Detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.503166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f18652ac-9a68-458d-9f9e-660efa03cfe0 · outbound

This paper cites Microsoft COCO: Common objects in context,.

2.5D Object Detection for Intelligent Roadside Infrastructure Microsoft COCO: Common objects in context,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.490034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0386a941-c0b4-4cef-af6d-3937c9ee2064 · outbound

This paper cites End-to-End Object Detection with Transformers,.

2.5D Object Detection for Intelligent Roadside Infrastructure End-to-End Object Detection with Transformers,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.475912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2dec63b3-2560-48d6-92e3-d34ee5139c44 · outbound

This paper cites DETRs with Collaborative Hybrid Assignments Training,.

2.5D Object Detection for Intelligent Roadside Infrastructure DETRs with Collaborative Hybrid Assignments Training,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.461118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5ed4dc9e-e15a-42d8-b1dc-10d08cde3a7e · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.447222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dd1d59a5-4e9a-44ef-936d-ed0287e2aa9b · outbound

This paper cites Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment,.

2.5D Object Detection for Intelligent Roadside Infrastructure Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.433471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b0994482-66cb-4a1f-871d-3efc30f86135 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure You Only Look Once: Unified, Real-Time Object Detection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.419444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c6062c24-4303-4655-9d48-ce016c8c27e4 · outbound

This paper cites YOLOv3: An Incremental Improvement.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv3: An Incremental Improvement

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T20:12:43.856256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a12f1b7d-1d85-44a1-b6a3-685901ffecb1 · outbound

This paper cites YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object De- tectors,.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object De- tectors,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.405365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4ab2d363-14e4-457d-a1bb-9f1dad4a80d9 · outbound

This paper cites YOLO by Ultralytics (Version 8.0.0),.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLO by Ultralytics (Version 8.0.0),

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.391943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 582930c0-0219-448e-9873-341121cdbc7d · outbound

This paper cites YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information,.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.378150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4572b198-250f-4c21-ac36-f86398758fc7 · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv10: Real-Time End-to-End Object Detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.364790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e3f5878e-1852-4406-ad2b-3d31e393c8b2 · outbound

This paper cites Ultralytics YOLO11,.

2.5D Object Detection for Intelligent Roadside Infrastructure Ultralytics YOLO11,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.351285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5a9e1396-8b92-48e6-911f-f3d4e684a6db · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T20:12:43.880702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd974c0a-d1e2-48d5-ba01-8bf7053cd0e0 · outbound

This paper cites DETRs Beat YOLOs on Real-time Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure DETRs Beat YOLOs on Real-time Object Detection,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.336784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 848e87dd-0662-4fa1-8c7a-5f2bdf91b2a4 · outbound

This paper cites RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer.

2.5D Object Detection for Intelligent Roadside Infrastructure RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T20:12:43.889059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0cda452-47cd-47df-9b5a-4caa0e032a73 · outbound

This paper cites RT-DETRv3: Real-time End-to- End Object Detection with Hierarchical Dense Positive Supervision,.

2.5D Object Detection for Intelligent Roadside Infrastructure RT-DETRv3: Real-time End-to- End Object Detection with Hierarchical Dense Positive Supervision,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.322903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cbef2292-fd0d-4f6e-9e63-bb7f7c13e3bf · outbound

This paper cites 3D Object Detection for Au- tonomous Driving: A Comprehensive Survey,.

2.5D Object Detection for Intelligent Roadside Infrastructure 3D Object Detection for Au- tonomous Driving: A Comprehensive Survey,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.308081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bfd34b1c-016e-47b1-816d-49021b6479f9 · outbound

This paper cites M3D-RPN: Monocular 3D Region Proposal Network for Object Detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure M3D-RPN: Monocular 3D Region Proposal Network for Object Detection,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.293511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3f2b901-0a61-4f08-a795-9f555cc92f7d · outbound

This paper cites FCOS: Fully convolutional one-stage object detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure FCOS: Fully convolutional one-stage object detection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.278846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3faec676-7d85-4076-bd01-3576136cac33 · outbound

This paper cites Inverse perspective mapping simplifies optical flow computation and obstacle detection,.

2.5D Object Detection for Intelligent Roadside Infrastructure Inverse perspective mapping simplifies optical flow computation and obstacle detection,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.263265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d1c781c1-5b3d-4b4f-ac53-100338e08be4 · outbound

This paper cites MIO-TCD: A New Benchmark Dataset for Vehicle Classification and Localization,.

2.5D Object Detection for Intelligent Roadside Infrastructure MIO-TCD: A New Benchmark Dataset for Vehicle Classification and Localization,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.246983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b72cea22-d149-4f0f-8348-35bb12d6a92a · outbound

This paper cites UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking,.

2.5D Object Detection for Intelligent Roadside Infrastructure UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.233201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 509af9ff-a394-47dd-812a-24bbab6afae0 · outbound

This paper cites Vehicle Tracking by Simul- taneous Detection and Viewpoint Estimation,.

2.5D Object Detection for Intelligent Roadside Infrastructure Vehicle Tracking by Simul- taneous Detection and Viewpoint Estimation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.218506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b0866b1c-60ab-41ac-a256-96876e7bd4e0 · outbound

This paper cites YOLOv7-3D: A Monocular 3D Traffic Object Detection Method from a Roadside Perspective,.

2.5D Object Detection for Intelligent Roadside Infrastructure YOLOv7-3D: A Monocular 3D Traffic Object Detection Method from a Roadside Perspective,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.204701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f5cc717d-a1ca-4699-98c7-19a7cc0efb65 · outbound

This paper cites Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task,.

2.5D Object Detection for Intelligent Roadside Infrastructure Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.190631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0ac7b9ba-0b91-4bac-866e-d31f018787d1 · outbound

This paper cites Optimal traffic control at smart intersections: Automated network fundamental diagram,.

2.5D Object Detection for Intelligent Roadside Infrastructure Optimal traffic control at smart intersections: Automated network fundamental diagram,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.174883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d9433698-925f-4457-a540-721e0340f59f · outbound

This paper cites TUMTraf Inter- section Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception,.

2.5D Object Detection for Intelligent Roadside Infrastructure TUMTraf Inter- section Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.160834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e099ff82-01db-4077-a394-0dbb5e3a655b · outbound

This paper cites From Traffic Sensor Data To Semantic Traffic Descriptions: The Test Area Au- tonomous Driving Baden-W ¨urttemberg Dataset (TAF-BW Dataset),.

2.5D Object Detection for Intelligent Roadside Infrastructure From Traffic Sensor Data To Semantic Traffic Descriptions: The Test Area Au- tonomous Driving Baden-W ¨urttemberg Dataset (TAF-BW Dataset),

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.146042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1610a3bc-3922-470e-b2f7-2f25a6f6af5c · outbound

This paper cites Semi-Automatic Ground Truth Trajectory Estimation and Smoothing using Roadside Cameras,.

2.5D Object Detection for Intelligent Roadside Infrastructure Semi-Automatic Ground Truth Trajectory Estimation and Smoothing using Roadside Cameras,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.131707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 733d0dfd-fcfa-4e0a-bf8d-d9b91464a9db · outbound

This paper cites Sekachev, N.

2.5D Object Detection for Intelligent Roadside Infrastructure Sekachev, N

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.116038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 07f8d50d-15d5-4343-9a47-070593487caa · outbound

This paper cites CARLA: An Open Urban Driving Simulator,.

2.5D Object Detection for Intelligent Roadside Infrastructure CARLA: An Open Urban Driving Simulator,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.101431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0f26eaf9-eae4-4ffa-b795-de616c788cba · outbound

This paper cites Distance-IoU loss: Faster and better learning for bounding box regression,.

2.5D Object Detection for Intelligent Roadside Infrastructure Distance-IoU loss: Faster and better learning for bounding box regression,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.087403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f3f93039-b455-4176-b436-679bad7c631f · outbound

This paper cites The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale,.

2.5D Object Detection for Intelligent Roadside Infrastructure The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.072569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 13954541-1453-406b-beeb-8243a4c30e97 · outbound

This paper cites Improving object detector training on synthetic data by starting with a strong baseline methodology,.

2.5D Object Detection for Intelligent Roadside Infrastructure Improving object detector training on synthetic data by starting with a strong baseline methodology,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:12:44.057732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 9852d006-b3b8-4c6d-85de-e4678eb45c81 · inbound

Ufil: A Unified Framework for Infrastructure-based Localization cites this paper.

Ufil: A Unified Framework for Infrastructure-based Localization 2.5D Object Detection for Intelligent Roadside Infrastructure

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:21:07.267518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.