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Paper Citation Record · LEDGER

Multi-View Reconstruction with Global Context for 3D Anomaly Detection

As of 19 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2507.21555.

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

pith.paper-citation-record.v1
2507.21555 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:43:22.772617Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact4
  • verified fuzzy8
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72410b8d-2549-423f-8057-20b506845a1e · outbound

This paper cites A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:23.531257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.073280Z digest=sha256:219c9321e293e747ab2ccb74ef9e24c12fa9042c57de3de555f416ca92a7b221

Observation 2c514148-dd4f-45e0-a9d5-7e77ce6b6a63 · outbound

This paper cites MVGR: Mean-variance minimization global registration method for multi-view point cloud in robot inspection,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection MVGR: Mean-variance minimization global registration method for multi-view point cloud in robot inspection,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:25.123232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.110483Z digest=sha256:ca9cfe44c92bb797f13d705150e7c6f613c46b83083cbc2a74332b993e1c3501

Observation 79c3dc5d-abdc-479c-bafa-9d73eabc90eb · outbound

This paper cites Complementary pseudo multimodal feature for point cloud anomaly detection,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Complementary pseudo multimodal feature for point cloud anomaly detection,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:24.919607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.251762Z digest=sha256:e17c2692c0fddbb49a5f0eb8c3d08b2a6fb798e29fcf5031e52982a9fb676919

Observation e1ec5628-4f2a-42a0-946c-7cd12c7fa443 · outbound

This paper cites Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:23.380614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.379209Z digest=sha256:cf01bd38b0911ba7517b37313dd0010491ad4cdac0cacaa88d85141b3726f7a3

Observation 872355a4-3671-4333-bb5a-603c7f27e1d9 · outbound

This paper cites Real3d-ad: A dataset of point cloud anomaly detection,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Real3d-ad: A dataset of point cloud anomaly detection,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:24.741461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.491972Z digest=sha256:714f95a7d0e1ab394f68686ba95fbbdaa822e28eae215e6aaa306a9abfd48a95

Observation d84dd927-a48f-4a6b-9cb4-42e05f77493c · outbound

This paper cites Towards high-resolution 3d anomaly detection via group-level feature contrastive learning,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Towards high-resolution 3d anomaly detection via group-level feature contrastive learning,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:24.598658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.594543Z digest=sha256:1823c24377883e0cd059e695641b988849da757520ebe7be8476f28bcaa8abdc

Observation 564b6939-8d8f-48bb-adeb-bc4db8e304b4 · outbound

This paper cites Boosting global- local feature matching via anomaly synthesis for multi-class point cloud anomaly detection,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Boosting global- local feature matching via anomaly synthesis for multi-class point cloud anomaly detection,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:24.305397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.710860Z digest=sha256:5fa60bb86dce5ce10faa094e042b1effa61610175dbd1960fbf7f5729245322a

Observation 985aee26-20b2-4ed5-a3f7-8b17a64e9fbd · outbound

This paper cites Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:21.825025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:21.825025Z digest=sha256:70f64dbcb5eeacb610da6d46091d5bf2cacaec298d14a77f097b88f81c7afdaa

Observation 3c7c81d9-c35c-48ae-9cfe-26ec64bce95a · outbound

This paper cites Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:23.205162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:21.986464Z digest=sha256:94334f1c1f7ee916d004347658d40c896c9cb2a471249790bfd07a6b88cb3d44

Observation 42a5d65d-585c-40d2-8aee-8bbb7662763e · outbound

This paper cites ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:22.107038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:22.107038Z digest=sha256:db54f6aec58c9d47a4d372dc3e6faf0eb5d286b4aafc7062582f67250b293d04

Observation 383ade19-95c3-47d7-b36c-0fd1401a43a3 · outbound

This paper cites Multimodal industrial anomaly detection via hybrid fusion,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Multimodal industrial anomaly detection via hybrid fusion,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:24.016073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:22.169626Z digest=sha256:1399ccc0659b3e562b3c6e0c6c724bd13d5d90f2b7661653fb0cc5cf5e874877

Observation 767d08cc-3de6-4166-adb6-8cacbd4e0057 · outbound

This paper cites R3d-ad: Reconstruction via diffusion for 3d anomaly detection,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection R3d-ad: Reconstruction via diffusion for 3d anomaly detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:23.858740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:22.266533Z digest=sha256:0bea4b8428be1cd22344032dda2448c578a80c9ebef886d82be1b67f468cf672

Observation 9a4aa0bf-3d74-4a45-85f3-7d1a8f80b39a · outbound

This paper cites Towards scalable 3d anomaly detection and localization: A benchmark via 3d anomaly synthesis and a self-supervised learning network,.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Towards scalable 3d anomaly detection and localization: A benchmark via 3d anomaly synthesis and a self-supervised learning network,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:43:23.737830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:22.319181Z digest=sha256:38b1f5483a828959b3b1159e15501e84d044427f925bf87257b920b4fc1cfa83

Observation 5b37ecd3-164b-487d-a09f-84771f6296c4 · outbound

This paper cites PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:22.977589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T12:43:22.402950Z digest=sha256:02466627728d97cc4372329e0f44f754c6ef1eb0d714f76e30826c8ead43aab9

Observation 23c179b9-8892-44db-a76b-636f51b00839 · outbound

This paper cites Open3D: A Modern Library for 3D Data Processing.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Open3D: A Modern Library for 3D Data Processing

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:22.510478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:22.510478Z digest=sha256:1ec90e4a5dae3eea8eebcbff74fd81d34cf2a73516daa94bb77e963891667994

Observation d4f38613-c242-4ac5-a4a4-b1580ea4f4b7 · outbound

This paper cites Vision Transformers Need Registers.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Vision Transformers Need Registers

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:22.608796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:22.608796Z digest=sha256:920b69be77c7d42679e21fd2f913f28556e7543d4edb100581421a0f84c1db56

Observation b9d16b61-1c68-4c3c-86ec-8696c9689ba5 · outbound

This paper cites Stable and low-precision training for large-scale vision-language models.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Stable and low-precision training for large-scale vision-language models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:22.675231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:22.675231Z digest=sha256:f8236e57e70712221a6b2530a2a2d3cc8c3617354642e7f1d45fbf3f1509bbfe

Observation 59498264-d046-47ad-8a9c-de64c41c2a4d · outbound

This paper cites On the Convergence of Adam and Beyond.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection On the Convergence of Adam and Beyond

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T12:43:22.772617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:43:22.772617Z digest=sha256:cf1a2a46977184204cd7c0eabf03d390e59f6e505ee4c5c7084461a8a63411a9

Pith citing papers

No inbound Pith citation observations are available.