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Paper Citation Record · LEDGER

Probabilistic and Geometric Depth: Detecting Objects in Perspective

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.14160.

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

pith.paper-citation-record.v1
2107.14160 v3

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:03:12.007827Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T14:35:28.693391Z

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 c908076c-ade0-45b2-8495-258bf9720259 · inbound

BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View cites this paper.

BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View Probabilistic and Geometric Depth: Detecting Objects in Perspective

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:35:28.696595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T14:35:28.633939Z digest=sha256:ad46fdfc28c1024063918f257c724fe8542fd7b5ee1848b9b82f04e8a6a00208

Observation 597088ce-675c-4c40-90c4-5894ca8aa5c9 · inbound

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception cites this paper.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Probabilistic and Geometric Depth: Detecting Objects in Perspective

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T19:03:12.007827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:12.007827Z digest=sha256:bdf8f1bd8df87ecc5b7017e6285606d161ebbad0c543531007687bf0b912a0e9