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Paper Citation Record · LEDGER

Towards Zero-shot 3D Anomaly Localization

As of 15 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2412.04304.

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

pith.paper-citation-record.v1
2412.04304 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:39:11.991039Z

measured 56 of 56 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 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

56 of 56 outbound references displayed

  • verified exact1
  • verified fuzzy45
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc6ac72a-3c59-44b0-8053-ad579e8e3815 · outbound

This paper cites Cross-domain video anomaly detection without target domain adaptation.

Towards Zero-shot 3D Anomaly Localization Cross-domain video anomaly detection without target domain adaptation

Reference 1

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Observation 6f7f0489-4c1f-4045-88bd-2726445d50bc · outbound

This paper cites MVTec AD–a comprehensive real-world dataset for un- supervised anomaly detection.

Towards Zero-shot 3D Anomaly Localization MVTec AD–a comprehensive real-world dataset for un- supervised anomaly detection

Reference 2

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Observation 1aff1221-31ea-4ee2-91d8-59b09710cf7f · outbound

This paper cites The MVTec 3D-AD dataset for unsupervised 3D anomaly detection and localization.

Towards Zero-shot 3D Anomaly Localization The MVTec 3D-AD dataset for unsupervised 3D anomaly detection and localization

Reference 3

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Observation a088803c-3f5f-4edf-b10b-4e2c07154807 · outbound

This paper cites Anomaly detection in 3D point clouds using deep geometric descriptors.

Towards Zero-shot 3D Anomaly Localization Anomaly detection in 3D point clouds using deep geometric descriptors

Reference 4

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

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Observation 8508c21d-8fc0-4d81-9070-74deb304728a · outbound

This paper cites Col- laborative discrepancy optimization for reliable image anomaly localization.

Towards Zero-shot 3D Anomaly Localization Col- laborative discrepancy optimization for reliable image anomaly localization

Reference 5

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

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Observation 3bd8bf7b-801e-4419-890f-f3b2d02a400c · outbound

This paper cites Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection.

Towards Zero-shot 3D Anomaly Localization Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection

Reference 6

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Source-reported events for the cited work

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Observation a0d6a0b8-40b7-4b4e-a3ff-a1ad5167ffb9 · outbound

This paper cites A random CNN sees objects: One inductive bias of cnn and its applications.

Towards Zero-shot 3D Anomaly Localization A random CNN sees objects: One inductive bias of cnn and its applications

Reference 7

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Source-reported events for the cited work

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Observation 5f126467-7fd7-4142-9a67-300f1943035d · outbound

This paper cites Transductive zero-shot learning for 3d point cloud classification.

Towards Zero-shot 3D Anomaly Localization Transductive zero-shot learning for 3d point cloud classification

Reference 8

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Observation c7f9acc6-5735-4e18-a76a-17d3059561e3 · outbound

This paper cites Zero-shot learning on 3d point cloud objects and beyond.International Journal of Computer V ision, 130(10):2364–2384, 2022.

Towards Zero-shot 3D Anomaly Localization Zero-shot learning on 3d point cloud objects and beyond.International Journal of Computer V ision, 130(10):2364–2384, 2022

Reference 9

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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.

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Observation 314e97e9-b635-43e0-a79f-68393b526a79 · outbound

This paper cites Shape-guided dual-memory learning for 3d anomaly detection.

Towards Zero-shot 3D Anomaly Localization Shape-guided dual-memory learning for 3d anomaly detection

Reference 10

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

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Observation 3af79dfe-79b9-4ff0-89ad-741ad0cb18ea · outbound

This paper cites Sub-Image Anomaly Detection with Deep Pyramid Correspondences.

Towards Zero-shot 3D Anomaly Localization Sub-Image Anomaly Detection with Deep Pyramid Correspondences

Reference 11

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Observation 07394c45-90ce-4a93-a458-292f7d1e405a · outbound

This paper cites PaDiM: a patch distribution modeling framework for anomaly detection and localization.

Towards Zero-shot 3D Anomaly Localization PaDiM: a patch distribution modeling framework for anomaly detection and localization

Reference 12

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

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Observation d926addb-6f12-458a-ae7e-250788c15b51 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Towards Zero-shot 3D Anomaly Localization Imagenet: A large-scale hierarchical image database

Reference 13

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Observation abf624f1-d7f5-4e47-bfa5-c5edee0bd481 · outbound

This paper cites Catching both gray and black swans: Open-set supervised anomaly detec- tion.

Towards Zero-shot 3D Anomaly Localization Catching both gray and black swans: Open-set supervised anomaly detec- tion

Reference 14

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Observation 0e50a731-0a2d-4361-b049-76c6371bc69f · outbound

This paper cites Zero-shot out-of-distribution detection based on the pre-trained model CLIP.

Towards Zero-shot 3D Anomaly Localization Zero-shot out-of-distribution detection based on the pre-trained model CLIP

Reference 15

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

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Observation 75533164-75c4-4163-9a4a-8c4362478d42 · outbound

This paper cites A graph-based one-shot learning method for point cloud recognition.

Towards Zero-shot 3D Anomaly Localization A graph-based one-shot learning method for point cloud recognition

Reference 16

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

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Observation af499338-6ab9-4888-a046-5bda68d4fefc · outbound

This paper cites Mpdnet: A 3d missing part detection network based on point cloud segmentation.

Towards Zero-shot 3D Anomaly Localization Mpdnet: A 3d missing part detection network based on point cloud segmentation

Reference 17

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Observation 3ea0a3c5-4c99-4881-85df-fe79a0504c56 · outbound

This paper cites Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit.

Towards Zero-shot 3D Anomaly Localization Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit

Reference 18

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Observation 7ddd538c-41d4-4a59-9504-6a8f7db847a3 · outbound

This paper cites Masked autoencoders are scalable vision learn- ers.

Towards Zero-shot 3D Anomaly Localization Masked autoencoders are scalable vision learn- ers

Reference 19

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Observation 995a3080-c2b0-49ab-a82d-f89875bfdad3 · outbound

This paper cites Delv- ing deep into rectifiers: Surpassing human-level performance on imagenet classification.

Towards Zero-shot 3D Anomaly Localization Delv- ing deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 20

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Observation bc04a583-ca8e-41fd-a721-4e3f1cce6caa · outbound

This paper cites Long-tailed anomaly detection with learnable class names.

Towards Zero-shot 3D Anomaly Localization Long-tailed anomaly detection with learnable class names

Reference 21

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Observation be404d69-d578-4bd9-95e1-04cc67e0c2f5 · outbound

This paper cites an unresolved cited work.

Towards Zero-shot 3D Anomaly Localization Unresolved cited work

Reference 22

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Observation 1218d2fc-f637-4266-b824-db890ac2664f · outbound

This paper cites Back to the feature: Classical 3d features are (almost) all you need for 3d anomaly detection.

Towards Zero-shot 3D Anomaly Localization Back to the feature: Classical 3d features are (almost) all you need for 3d anomaly detection

Reference 23

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Observation cc788152-8ab6-4c37-826d-5b0c3a26f218 · outbound

This paper cites Registration based few-shot anomaly detection.

Towards Zero-shot 3D Anomaly Localization Registration based few-shot anomaly detection

Reference 24

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Observation 9ac8df4c-1a6f-45d1-b9b5-8e00b65e8a0f · outbound

This paper cites Winclip: Zero-/few- shot anomaly classification and segmentation.

Towards Zero-shot 3D Anomaly Localization Winclip: Zero-/few- shot anomaly classification and segmentation

Reference 25

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Observation 173f363a-7609-478a-96ca-75968ac26f43 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Towards Zero-shot 3D Anomaly Localization Adam: A Method for Stochastic Optimization

Reference 26

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Source-reported events for the cited work

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Observation 3c4e20c7-df2c-43d0-9aba-e13e627f25bd · outbound

This paper cites V andermeulen, Billy Joe Franks, Marius Kloft, and Klaus Robert Muller.

Towards Zero-shot 3D Anomaly Localization V andermeulen, Billy Joe Franks, Marius Kloft, and Klaus Robert Muller

Reference 27

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Observation 19b5f314-ff16-429e-9608-ca42115cd8b5 · outbound

This paper cites V andermeulen, Billy Joe Franks, Klaus Robert Muller, and Marius Kloft.

Towards Zero-shot 3D Anomaly Localization V andermeulen, Billy Joe Franks, Klaus Robert Muller, and Marius Kloft

Reference 28

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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.

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Observation 1857dcd7-bc41-498d-be7f-75f0de73328f · outbound

This paper cites Few-shot scene-adaptive anomaly detection.

Towards Zero-shot 3D Anomaly Localization Few-shot scene-adaptive anomaly detection

Reference 29

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

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Observation b9bdba50-e8ba-406d-a86a-626d1f93b308 · outbound

This paper cites Toward unsupervised 3D point cloud anomaly detection using variational autoencoder.

Towards Zero-shot 3D Anomaly Localization Toward unsupervised 3D point cloud anomaly detection using variational autoencoder

Reference 30

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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.

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Observation 5de55a20-f5bc-4bc6-b264-4d26aed097da · outbound

This paper cites Explainable Deep Few-shot Anomaly Detection with Deviation Networks.

Towards Zero-shot 3D Anomaly Localization Explainable Deep Few-shot Anomaly Detection with Deviation Networks

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c70182d7-3787-4ae9-baaa-1c062b032182 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.

Towards Zero-shot 3D Anomaly Localization Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 32

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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.

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Observation cedd513a-6b69-47ed-ae0c-0f063ac2f89c · outbound

This paper cites Learning transferable visual models from natural language supervision.

Towards Zero-shot 3D Anomaly Localization Learning transferable visual models from natural language supervision

Reference 33

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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.

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Observation c9fc8545-29b6-40ae-82af-6abf419dbf19 · outbound

This paper cites Towards total recall in industrial anomaly detection.

Towards Zero-shot 3D Anomaly Localization Towards total recall in industrial anomaly detection

Reference 34

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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.

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Observation 23bc0b47-9a73-44f9-869f-d17ef395c7c5 · outbound

This paper cites Asymmetric student-teacher networks for industrial anomaly detection.

Towards Zero-shot 3D Anomaly Localization Asymmetric student-teacher networks for industrial anomaly detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.482833Z

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=2026-08-11T21:39:11.901993Z digest=sha256:90a89f68367c2c4bb3a2756018892247143a8fddbfe83b1cb4d4767d9b9be878

Observation 3d795b78-de63-49c9-92ca-956b8a98d8b2 · outbound

This paper cites Fast point feature histograms (fpfh) for 3d registration.

Towards Zero-shot 3D Anomaly Localization Fast point feature histograms (fpfh) for 3d registration

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.471271Z

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=2026-08-11T21:39:11.906269Z digest=sha256:1ab68f682a6854222dffd98c8c55087680f5ee7e463289f7a9fd644fa97f60ca

Observation b7d805e4-d138-4b1a-a542-169f1d3891e0 · outbound

This paper cites Maeday: Mae for few- and zero-shot anomaly-detection.Computer V ision and Image Understanding, 241:103958, 2024.

Towards Zero-shot 3D Anomaly Localization Maeday: Mae for few- and zero-shot anomaly-detection.Computer V ision and Image Understanding, 241:103958, 2024

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.459684Z

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=2026-08-11T21:39:11.910023Z digest=sha256:6c5ca7fe5c43fb3dc942a820bde2a5bbf1877556bce0ed211f9e68e600753bc8

Observation dc3428a0-ce54-4e3c-acc9-d699c2f8a4c0 · outbound

This paper cites Active learning for convolu- tional neural networks: A core-set approach.

Towards Zero-shot 3D Anomaly Localization Active learning for convolu- tional neural networks: A core-set approach

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.447898Z

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=2026-08-11T21:39:11.913732Z digest=sha256:71941e2a052106794152fedc02c170d4f7d7efe2edff1c25d5136fae4a521004

Observation 6060fd0c-f7e9-43c0-97e1-50d8deda8263 · outbound

This paper cites A hierarchi- cal transformation-discriminating generative model for few shot anomaly detection.

Towards Zero-shot 3D Anomaly Localization A hierarchi- cal transformation-discriminating generative model for few shot anomaly detection

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.434462Z

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=2026-08-11T21:39:11.917898Z digest=sha256:6d2f09974ce32f400db945f5e8f6ee577d60653767e051db94de3cdfcb5eaa2f

Observation ff350d1f-1a42-4747-877a-ddb31d588081 · outbound

This paper cites Small-gan: Speeding up gan training using core-sets.

Towards Zero-shot 3D Anomaly Localization Small-gan: Speeding up gan training using core-sets

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.420162Z

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=2026-08-11T21:39:11.921825Z digest=sha256:427d610239ad184f79cccbca428387ad5eba96b5ec0168083072e27740da88fa

Observation 4810b86d-7314-4277-9dba-643ea0e1328b · outbound

This paper cites Attention guided anomaly localization in images.

Towards Zero-shot 3D Anomaly Localization Attention guided anomaly localization in images

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.408371Z

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=2026-08-11T21:39:11.926375Z digest=sha256:43a86f2d63afc617ad2341af09287137ba69266d6014f825a3c4a96f75369d0d

Observation b5502693-3330-4139-9087-ec2c976a2411 · outbound

This paper cites Position encoding enhanced feature mapping for image anomaly detection.

Towards Zero-shot 3D Anomaly Localization Position encoding enhanced feature mapping for image anomaly detection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.396331Z

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=2026-08-11T21:39:11.930281Z digest=sha256:9d047455bffa1e5f2e3f96218e42e84e6c1f4d6b5ef0bd90f46c12d066178569

Observation 04ccb50b-7791-4e9d-9d27-3fa794a88b99 · outbound

This paper cites Unveiling the Unseen: A Comprehensive Survey on Explainable Anomaly Detection in Images and Videos.

Towards Zero-shot 3D Anomaly Localization Unveiling the Unseen: A Comprehensive Survey on Explainable Anomaly Detection in Images and Videos

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-11T21:39:12.205682Z

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=2026-08-11T21:39:11.934720Z digest=sha256:7c0fc18156b138c96e865a316ac9bc564a936bb1fc35232b03aef67ffd3be9be

Observation 841e264d-f887-4b88-b78c-e3e46b0af419 · outbound

This paper cites Multimodal industrial anomaly detection via hybrid fusion.

Towards Zero-shot 3D Anomaly Localization Multimodal industrial anomaly detection via hybrid fusion

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.384875Z

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=2026-08-11T21:39:11.939816Z digest=sha256:69ab0750b6f84802fe0d3f5ca23b3542ea729a1692a91072fc514ce89ad1bc0e

Observation fd4a658b-0260-4c32-b051-baaf74a774b7 · outbound

This paper cites Making reconstruction-based method great again for video anomaly detection.

Towards Zero-shot 3D Anomaly Localization Making reconstruction-based method great again for video anomaly detection

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.369146Z

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=2026-08-11T21:39:11.944136Z digest=sha256:5bcf9def5b68340891d9bcc65b47dc259a869130e589bf9c1cf8860e1ba46509

Observation 6333856e-ff4e-41c2-88b2-e3dd424b72d1 · outbound

This paper cites Self-supervision meets adversarial perturbation: A novel framework for anomaly detection.

Towards Zero-shot 3D Anomaly Localization Self-supervision meets adversarial perturbation: A novel framework for anomaly detection

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.355923Z

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=2026-08-11T21:39:11.948536Z digest=sha256:c126c000a6e28cdd9c8f5b330fd3b5f52cdf9be0a5675e51eb29d40fe5f8db32

Observation a9356545-f0be-4ffb-90be-e53a3d3b46ac · outbound

This paper cites Sla22p: Self-supervised anomaly detection with adversarial perturbation.

Towards Zero-shot 3D Anomaly Localization Sla22p: Self-supervised anomaly detection with adversarial perturbation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.344531Z

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=2026-08-11T21:39:11.952663Z digest=sha256:609ce3977bf1777e03cd7ab3973b0960ce44b1401f9c49a4689531333b739bb5

Observation 494a8e5e-6413-48ad-b3ef-0420a62274f9 · outbound

This paper cites Learning unsupervised metaformer for anomaly detection.

Towards Zero-shot 3D Anomaly Localization Learning unsupervised metaformer for anomaly detection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.329585Z

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=2026-08-11T21:39:11.956445Z digest=sha256:5645d34e6ecef21a79a6b09dcac2a683d66bab8ca0e1d58fae819a9881019e53

Observation 7797a902-fc47-4ea4-8bd7-1c639d248dd7 · outbound

This paper cites IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing.

Towards Zero-shot 3D Anomaly Localization IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T21:39:11.961534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.961534Z digest=sha256:d95eb8d15291b6aae3277e34021c58baa6ec8411a9bb0598ed1745c5d2eb0724

Observation bc8d1841-41bd-4524-9e8d-be16688b2613 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

Towards Zero-shot 3D Anomaly Localization Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.314969Z

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=2026-08-11T21:39:11.966567Z digest=sha256:122730a83d75433516ba65c412b7c85c01e615c19604c20392986df062f959e3

Observation 115a6e37-7a7f-4b30-a976-a034b7d296f8 · outbound

This paper cites Wide residual networks.

Towards Zero-shot 3D Anomaly Localization Wide residual networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.298530Z

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=2026-08-11T21:39:11.970723Z digest=sha256:c95baf01d29d39d49901c83fa50cd14d425ceb1da2d0052baeba61101c4ac6d1

Observation 74110194-1483-4fb2-b9db-b05fb5f0b00a · outbound

This paper cites an unresolved cited work.

Towards Zero-shot 3D Anomaly Localization Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-11T21:39:12.287119Z

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=2026-08-11T21:39:11.974722Z digest=sha256:a3fd25babdee313b7c976a8d579c1a3b12de43fe47b5d051262c53a66c21f59a

Observation 252c288e-6968-452b-b103-93e704210504 · outbound

This paper cites Cheating depth: Enhancing 3d surface anomaly detection via depth simulation.

Towards Zero-shot 3D Anomaly Localization Cheating depth: Enhancing 3d surface anomaly detection via depth simulation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.275603Z

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=2026-08-11T21:39:11.978589Z digest=sha256:fa3db1d370183dcb7494bf0443b75f491c6f8d99e40093360626e266328e6491

Observation 88d0d156-4086-4d4e-99f6-5d03c7a01562 · outbound

This paper cites Benchmarking Unsupervised Anomaly Detection and Localization.

Towards Zero-shot 3D Anomaly Localization Benchmarking Unsupervised Anomaly Detection and Localization

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T21:39:11.983267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.983267Z digest=sha256:601b44cab56a335b32d01f2647d434a694345f62b430f02979e81987cb7ee2ad

Observation d2ce7fe6-f364-43fd-9621-117dd0b880e5 · outbound

This paper cites Real-time kd-tree construction on graphics hardware.ACM Transactions on Graphics (TOG), 27(5):1–11, 2008.

Towards Zero-shot 3D Anomaly Localization Real-time kd-tree construction on graphics hardware.ACM Transactions on Graphics (TOG), 27(5):1–11, 2008

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.263558Z

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=2026-08-11T21:39:11.987285Z digest=sha256:576a489b5c16f14f035e37b22bcfa768c99c86f64f437b3af9ea68fc36e6f901

Observation 5de2d4a4-2e47-44ba-9e1b-2278e0f557fa · outbound

This paper cites Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection.arXiv preprint arXiv:2310.18961,.

Towards Zero-shot 3D Anomaly Localization Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection.arXiv preprint arXiv:2310.18961,

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T21:39:11.991039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.991039Z digest=sha256:6d6ad53a023e8e98269321b80af97e90c4b233d6e3918ae355af0c655bcb1837

Pith citing papers

No inbound Pith citation observations are available.