Pith. sign in

Paper Citation Record · LEDGER

Learning Deep Representations of Appearance and Motion for Anomalous Event Detection

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1510.01553.

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

pith.paper-citation-record.v1
1510.01553 v1

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 2026-08-06T12:34:00.575712Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-14T20:47:58.027759Z

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 a0cd8061-5aed-4fd8-a0b9-a2841b09cadc · inbound

The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM cites this paper.

The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM Learning Deep Representations of Appearance and Motion for Anomalous Event Detection

Reference 125

Resolution
unresolved
no resolver link, observed 2026-08-06T12:34:00.575712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:34:00.575712Z digest=sha256:ba57cc9e2e0f3debd0c2ace9fa584a32d139b995123e8326c390d7cb285d133e

Observation fd5150de-e0f3-4445-b715-6e29ccfc1181 · inbound

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models cites this paper.

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models Learning Deep Representations of Appearance and Motion for Anomalous Event Detection

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-05-14T20:47:58.030646Z

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=2026-05-14T20:47:08.389911Z digest=sha256:98bc519882526d2a6787698e87270aceabcdc0aaf4d0705076f97b5f1fe14650