Pith. sign in

Paper Citation Record · LEDGER

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1906.01140.

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

pith.paper-citation-record.v1
1906.01140 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:00:01.676494Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T00:45:09.237074Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0d3b362c-6122-46ad-93c7-4341d5d2f8aa · inbound

A review on deep learning techniques for 3D sensed data classification cites this paper.

A review on deep learning techniques for 3D sensed data classification Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:45:09.240675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-25T00:44:04.423996Z digest=sha256:0ea37d6f4785a11ddbbd931cb9903582c471e9316613215dead67124da696032

Observation 809fd4a7-e7bd-4f84-826c-c9ad65085c97 · inbound

Improving the Transferability of 3D Point Cloud Attack via Spectral-aware Admix and Optimization Designs cites this paper.

Improving the Transferability of 3D Point Cloud Attack via Spectral-aware Admix and Optimization Designs Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-11T14:00:01.676494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:00:01.676494Z digest=sha256:c22d132938c2e085a6a338ae8fc67f816e08c64f1362c55e43beab56531e7d65