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Paper Citation Record · LEDGER

Making a Case for 3D Convolutions for Object Segmentation in Videos

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2008.11516.

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

pith.paper-citation-record.v1
2008.11516 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:07:17.500179Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T11:47:46.106377Z

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 9de76fb1-51da-4540-9a14-3ed5f4f97e39 · inbound

TransFlow: Motion Knowledge Transfer from Video Diffusion Models to Video Salient Object Detection cites this paper.

TransFlow: Motion Knowledge Transfer from Video Diffusion Models to Video Salient Object Detection Making a Case for 3D Convolutions for Object Segmentation in Videos

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:04:50.243162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:04:50.243162Z digest=sha256:e975875e1571b9b05de7cecc1a54a12037bb05b40936b1c6f3d59551ce4f9fa0

Observation 88bfcf9f-993e-460d-8caf-53305a141f78 · inbound

DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation cites this paper.

DepthFlow: Exploiting Depth-Flow Structural Correlations for Unsupervised Video Object Segmentation Making a Case for 3D Convolutions for Object Segmentation in Videos

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T14:07:17.500179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:07:17.500179Z digest=sha256:6ca58bd9e2d9a8b3309beb66eeffe46ca95544d238905bfb714716cbca93eb8c

Observation 9cfcff7d-76a9-467a-a003-1449585b33b0 · inbound

Shallow Features Matter: Hierarchical Memory with Heterogeneous Interaction for Unsupervised Video Object Segmentation cites this paper.

Shallow Features Matter: Hierarchical Memory with Heterogeneous Interaction for Unsupervised Video Object Segmentation Making a Case for 3D Convolutions for Object Segmentation in Videos

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:47:46.174303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:47:42.437504Z digest=sha256:0ea05f2e3e46360f4639fb965868ac6fb494a2e8b5a873ee9792ba6a1982ac73