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Paper Citation Record · LEDGER

BodyNet: Volumetric Inference of 3D Human Body Shapes

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1804.04875.

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

pith.paper-citation-record.v1
1804.04875 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:14:01.004469Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T12:45:11.596746Z

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 eb14c281-e69b-467b-ac98-a34538583f17 · inbound

Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks cites this paper.

Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks BodyNet: Volumetric Inference of 3D Human Body Shapes

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T15:14:01.004469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:14:01.004469Z digest=sha256:a27a863b517154c7b434c9089cd031255f1a9609f6c7b562ac96ccf49c6b6474

Observation d99129a0-5360-403b-b2f0-99d9495ea968 · inbound

HumanMeshNet: Polygonal Mesh Recovery of Humans cites this paper.

HumanMeshNet: Polygonal Mesh Recovery of Humans BodyNet: Volumetric Inference of 3D Human Body Shapes

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-14T12:45:11.601932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T12:45:11.456966Z digest=sha256:fb22a9615b8d003b851590e2766c7f7631bee73b49feb17a0e284f454bc2c126