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Paper Citation Record · LEDGER

3D Bounding Box Estimation Using Deep Learning and Geometry

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1612.00496.

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

pith.paper-citation-record.v1
1612.00496 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:31:50.528054Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T12:31:50.596858Z

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 99c27220-2a4a-4717-8598-9949d18555e2 · inbound

BoxNet: A Deep Learning Method for 2D Bounding Box Estimation from Bird's-Eye View Point Cloud cites this paper.

BoxNet: A Deep Learning Method for 2D Bounding Box Estimation from Bird's-Eye View Point Cloud 3D Bounding Box Estimation Using Deep Learning and Geometry

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-14T12:31:50.603657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-14T12:31:50.528054Z digest=sha256:0c25e7fd20e2fbe1bdad77692092d5d160d68010611a805ea23fdd161da547bd