Paper Citation Record · LEDGER

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain

As of 12 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2501.18162.

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

pith.paper-citation-record.v1
2501.18162 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:32:20.281649Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy13
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4df384dc-83a5-436d-b7a7-f23369d1a13b · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.818115Z

Source-reported events for the cited work

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

Observation c5e5e363-eae9-4183-92a6-2ede19541ba3 · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain V2x-seq: A large- scale sequential dataset for vehicle-infrastructure cooperative percep- tion and forecasting,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.187007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11cfae4e-08b8-47af-8f4d-4034e7bb776a · outbound

This paper cites Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.191566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58016fc1-97fc-4539-85ab-5c4e3a98120c · outbound

This paper cites Bevheight: A robust framework for vision-based roadside 3d object detection,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Bevheight: A robust framework for vision-based roadside 3d object detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.793571Z

Source-reported events for the cited work

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

Observation 627416d2-d587-4a03-a257-15ba08344d8c · outbound

This paper cites Vision meets robotics: The kitti dataset,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Vision meets robotics: The kitti dataset,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.200715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e99ee365-45aa-4ab7-a2df-02fda0b95ac2 · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain nuScenes: A multimodal dataset for autonomous driving

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.204612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53e705bd-ef33-405a-bb78-4ee3bf167bec · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Scalability in perception for autonomous driving: Waymo open dataset,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.775997Z

Source-reported events for the cited work

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

Observation d045f364-9e99-4be9-b5c8-7b04c71dc3c3 · outbound

This paper cites Faster R-CNN: towards real-time object detection with region proposal networks,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Faster R-CNN: towards real-time object detection with region proposal networks,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.212806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad23501d-9131-42a3-94da-9a5a07655e9e · outbound

This paper cites Focal loss for dense object detection,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Focal loss for dense object detection,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.216054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76ff59f9-0a10-4587-8cb1-763e4daca768 · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Fcos: Fully convolutional one- stage object detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.764402Z

Source-reported events for the cited work

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

Observation 3f883091-d035-4f44-9754-c1523d75002f · outbound

This paper cites Objects as Points.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Objects as Points

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.223005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 205dcb95-cfaa-403e-a11a-47b3868a143f · outbound

This paper cites Attention is all you need,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Attention is all you need,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.226725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41506891-80f9-4bd8-bdbf-04153900ed02 · outbound

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

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain End-to-end object detection with transformers,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.230031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a657604-24ea-414f-8b38-77e3657e089c · outbound

This paper cites Deformable DETR: deformable transformers for end-to-end object detection,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Deformable DETR: deformable transformers for end-to-end object detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.739408Z

Source-reported events for the cited work

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

Observation c81b1ca0-187a-4c33-b75f-1259e066fe30 · outbound

This paper cites Monodetr: Depth-guided transformer for monocular 3d object detection,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Monodetr: Depth-guided transformer for monocular 3d object detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.729629Z

Source-reported events for the cited work

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

Observation a2b33b19-fd9f-4bf6-9ef6-9b8ced32c44a · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain A simple framework for contrastive learning of visual representations,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.720005Z

Source-reported events for the cited work

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

Observation 68a6adf1-b345-47fd-b324-a5e47761c76a · outbound

This paper cites Aligning pretraining for detection via object-level contrastive learning,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Aligning pretraining for detection via object-level contrastive learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.709951Z

Source-reported events for the cited work

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

Observation d56585d3-f3bc-4301-a0c4-da7d5fe81e97 · outbound

This paper cites Simipu: Simple 2d image and 3d point cloud unsupervised pre-training for spatial-aware visual representations,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Simipu: Simple 2d image and 3d point cloud unsupervised pre-training for spatial-aware visual representations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.698190Z

Source-reported events for the cited work

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

Observation fe8c730c-d222-4e64-baaa-317bb3161af9 · outbound

This paper cites 4dcontrast: Contrastive learning with dynamic correspondences for 3d scene understanding,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain 4dcontrast: Contrastive learning with dynamic correspondences for 3d scene understanding,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.253696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db7f7067-93f4-412f-9aea-8c9eb16d2e2c · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Momentum contrast for unsupervised visual representation learning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.257846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35046b36-ef38-4d9c-9a20-6e1d26ca9bb3 · outbound

This paper cites Contrastive multiview coding,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Contrastive multiview coding,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.261637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba194ff-a798-4e4d-80c8-2a105b143c8f · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Unsupervised learning of visual features by contrasting cluster assignments,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.686188Z

Source-reported events for the cited work

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

Observation 78b0485f-f7fa-4201-8ad7-9cb0a555a85b · outbound

This paper cites Bootstrap your own latent - A new approach to self-supervised learning,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Bootstrap your own latent - A new approach to self-supervised learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.674337Z

Source-reported events for the cited work

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

Observation 13bce15c-83d8-4fe1-80c2-5963796a0791 · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Dense contrastive learning for self-supervised visual pre-training,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.662519Z

Source-reported events for the cited work

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

Observation 09345225-28cc-4129-b549-a1db0a0f0f6c · outbound

This paper cites Coˆ 3: Cooperative unsupervised 3d representation learning for autonomous driving,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Coˆ 3: Cooperative unsupervised 3d representation learning for autonomous driving,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T00:32:20.277551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad5a722-4089-4eda-a00c-e6433caa3ebe · outbound

This paper cites Deep residual learning for image recognition,.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain Deep residual learning for image recognition,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T00:32:20.651078Z

Source-reported events for the cited work

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

Observation 33d3f34f-80ac-459f-b2c1-4c5193fda7c6 · outbound

This paper cites 1500–1508.

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain 1500–1508

Reference 2022

Resolution: verified exact; doi, observed 2026-08-10T00:32:20.327948Z

Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.