Paper Citation Record · LEDGER

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2507.02899.

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

pith.paper-citation-record.v1
2507.02899 v3

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:22.908863Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

19 of 19 outbound references displayed

verified exact0
verified fuzzy8
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0fa2fd95-c221-4fc1-b23e-a83fc3b28169 · outbound

This paper cites Loam: Lidar odometry and mapping in real-time.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Loam: Lidar odometry and mapping in real-time

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:23.140285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8ed2b8a0-ceb8-4dbc-9ff3-30721c2cdc4b · outbound

This paper cites Lego-loam: Lightweight and ground- optimized lidar odometry and mapping on variable terrain,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Lego-loam: Lightweight and ground- optimized lidar odometry and mapping on variable terrain,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.856009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffaa4097-31e3-4e2e-a48f-c3d1eb7aff6d · outbound

This paper cites Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:23.051511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bbf29ff4-39bc-497c-86e1-ec74289b14e6 · outbound

This paper cites Hdmapnet: An online hd map construction and evaluation framework,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Hdmapnet: An online hd map construction and evaluation framework,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.861715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3af64d83-302f-4dba-9983-740b1deedeb0 · outbound

This paper cites Vectormapnet: End-to-end vectorized hd map learning,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Vectormapnet: End-to-end vectorized hd map learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.865093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a59ea62d-2fa4-4969-974b-d1667da47735 · outbound

This paper cites MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.868333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a62f3e02-9d67-45e2-81be-47529decab39 · outbound

This paper cites Vi-map: Infrastructure-assisted real-time hd mapping for autonomous driving,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Vi-map: Infrastructure-assisted real-time hd mapping for autonomous driving,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.872149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a661d0e9-21bb-4792-8e89-aeec737545cf · outbound

This paper cites Deep residual learning for image recognition,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Deep residual learning for image recognition,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.874841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac1f6b22-e1ab-4cdf-9b07-54d3905c73af · outbound

This paper cites Efficientdet: Scalable and efficient object detection,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Efficientdet: Scalable and efficient object detection,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.877627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b622d032-8a47-41a3-903c-ed95fc788592 · outbound

This paper cites Path aggregation network for instance segmentation,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Path aggregation network for instance segmentation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:23.016865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd4ee98a-b979-4876-a424-03869bb94fc0 · outbound

This paper cites BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.884613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff066392-935f-4810-8998-8dd137e099f6 · outbound

This paper cites Cross-view transformers for real-time map-view semantic segmentation,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Cross-view transformers for real-time map-view semantic segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:23.007678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b92ca45a-199d-43b4-b26a-fb52b2f57da6 · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.890814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f77bb9e-58fc-4971-8df9-3ac23ad9d09b · outbound

This paper cites Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.893753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d34b6d46-35a7-4b7b-a659-44b4d055e3f6 · outbound

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

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Inverse perspective mapping simplifies optical flow computation and obstacle detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:22.993889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d861f75-7693-4dd8-9ec6-423ae9b250a1 · outbound

This paper cites Spatial transformer networks,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Spatial transformer networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:22.985014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 55e3f8c2-8f82-4f43-bccf-3d7bd706b71f · outbound

This paper cites Focal loss for dense object detection,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Focal loss for dense object detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:22.975791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f46991c5-8983-4ffa-b1a2-6783ea4d8383 · outbound

This paper cites Transforming between wgs84 realizations,.

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras Transforming between wgs84 realizations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:22.965346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2e935086-a94c-4407-8144-593864ceba9e · outbound

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

Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras nuscenes: A multimodal dataset for autonomous driving,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:22.908863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.