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Paper Citation Record · LEDGER

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection

As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2506.18544.

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

pith.paper-citation-record.v1
2506.18544 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:51:47.560314Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

68 of 68 outbound references displayed

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  • verified fuzzy57
  • unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 993276c8-8575-44dc-8e3e-47474519ff87 · outbound

This paper cites Unsupervised machine anomaly detection using autoencoder and temporal convolutional net- work,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Unsupervised machine anomaly detection using autoencoder and temporal convolutional net- work,

Reference 1

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 93205259-9e04-4812-97c2-4d1636296197 · outbound

This paper cites Vitalnet: Anomaly on industrial textured surfaces with hybrid transformer,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Vitalnet: Anomaly on industrial textured surfaces with hybrid transformer,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 709befe8-af23-475b-b48a-b85fe00e69db · outbound

This paper cites Deep one-class classifi- cation via interpolated gaussian descriptor,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Deep one-class classifi- cation via interpolated gaussian descriptor,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7d565d44-d9f0-417d-85d8-fe0cd2dabed6 · outbound

This paper cites Gan-based anomaly detection: A review,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Gan-based anomaly detection: A review,

Reference 4

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Source-reported events for the cited work

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Observation e2e8be2f-8113-4912-8e76-be2a3dd9d3ce · outbound

This paper cites Cloud-edge coordinated traffic anomaly detection for industrial cyber-physical systems,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Cloud-edge coordinated traffic anomaly detection for industrial cyber-physical systems,

Reference 5

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Observation 62ad7b54-1aa5-4c04-95e8-e28807a28268 · outbound

This paper cites Itran: A novel transformer-based approach for industrial anomaly detection and local- ization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Itran: A novel transformer-based approach for industrial anomaly detection and local- ization,

Reference 6

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Source-reported events for the cited work

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Observation d7923fcf-cb8f-4b0a-8002-d5890fe67391 · outbound

This paper cites Crowded scene analysis: A survey,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Crowded scene analysis: A survey,

Reference 7

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Observation 0b38985c-3471-474c-8cb3-4d0eb31dffbf · outbound

This paper cites Feature retention guidance-based asymmet- ric distillation network for industrial precision surface defect detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Feature retention guidance-based asymmet- ric distillation network for industrial precision surface defect detection,

Reference 8

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Source-reported events for the cited work

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Observation f76d54ce-c5dc-4cba-bb95-0ff9c3af4617 · outbound

This paper cites Towards total recall in industrial anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Towards total recall in industrial anomaly detection,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation be7a4e6f-0a25-4440-baad-daa85ff96930 · outbound

This paper cites Anomaly-gan: A data augmentation method for train surface anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Anomaly-gan: A data augmentation method for train surface anomaly detection,

Reference 10

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ca3d2615-6f40-415c-a696-66e01f37a781 · outbound

This paper cites Discriminative feature learning framework with gradient preference for anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Discriminative feature learning framework with gradient preference for anomaly detection,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ea39373c-6552-45b1-823c-e87c645afa57 · outbound

This paper cites Be- yond dents and scratches: Logical constraints in unsupervised anomaly detection and localization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Be- yond dents and scratches: Logical constraints in unsupervised anomaly detection and localization,

Reference 12

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7d4bb54f-a615-4e12-abdd-770ccb7ce606 · outbound

This paper cites Panda: Adapting pretrained features for anomaly detection and segmentation,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Panda: Adapting pretrained features for anomaly detection and segmentation,

Reference 13

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 19e4cb51-37ff-43c3-beb8-e1299986f676 · outbound

This paper cites Learning memory-guided normality for anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Learning memory-guided normality for anomaly detection,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fed85d98-4544-4d12-8325-79402867d285 · outbound

This paper cites Visual anomaly detection via partition memory bank module and error estimation,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Visual anomaly detection via partition memory bank module and error estimation,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation afcb8fe6-1dad-4a08-98d6-0e9cac19959d · outbound

This paper cites Self-attention memory- augmented wavelet-cnn for anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Self-attention memory- augmented wavelet-cnn for anomaly detection,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ca1f1e2c-7a59-4c0a-9e7c-96ea6ce1ea94 · outbound

This paper cites Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 17

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation dd41bf2b-3497-4117-99e4-c4a9c576566a · outbound

This paper cites Anomaly detection via reverse distillation from one-class embedding,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Anomaly detection via reverse distillation from one-class embedding,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 946b4dbe-1c5c-4465-a488-af4da2b7975f · outbound

This paper cites Generative neural networks for anomaly detection in crowded scenes,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Generative neural networks for anomaly detection in crowded scenes,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4fceba68-65ec-455c-8390-57ec7e92d06b · outbound

This paper cites Template-guided hierarchical feature restoration for anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Template-guided hierarchical feature restoration for anomaly detection,

Reference 20

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9b670622-d0b3-4310-9f62-b490a218e923 · outbound

This paper cites Pointwise motion image (pmi): A novel motion representation and its applications to abnormality detection and behavior recognition,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Pointwise motion image (pmi): A novel motion representation and its applications to abnormality detection and behavior recognition,

Reference 21

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Source-reported events for the cited work

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Observation e3225952-32a5-410a-a159-d8d3539986a4 · outbound

This paper cites Memorizing structure-texture correspondence for image anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Memorizing structure-texture correspondence for image anomaly detection,

Reference 22

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0e69ebd2-ecb6-4e99-a1e9-2d2404f27712 · outbound

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

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Learning transferable visual models from natural language supervision,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ffb2da41-35a0-4a7b-9d8c-8173fd00dac8 · outbound

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

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Sub-Image Anomaly Detection with Deep Pyramid Correspondences

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dbd015a5-4aab-42ba-b1e4-4aa13f7e69d5 · outbound

This paper cites Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.363432Z digest=sha256:22fa4d7081277adde2839a20ad003b4ac63aa0a01eb364640ec2d827c68190af

Observation 34d3be81-5ff2-42b1-a015-6db754ebf3e5 · outbound

This paper cites Student-Teacher Feature Pyramid Matching for Anomaly Detection.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Student-Teacher Feature Pyramid Matching for Anomaly Detection

Reference 26

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no resolver link, observed 2026-08-15T18:51:47.367488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.367488Z digest=sha256:2125b66226eb8f4e17b42ba6d1eefc6b98e99c3ebaf1eb3fcbd58f57320ebf3c

Observation 4b724662-a627-48c2-bcfd-9b391f1840f9 · outbound

This paper cites Multiresolution knowledge distillation for anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Multiresolution knowledge distillation for anomaly detection,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b6c9f63f-5216-4985-b309-31248c4b1b87 · outbound

This paper cites Ganomaly: Semi- supervised anomaly detection via adversarial training,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Ganomaly: Semi- supervised anomaly detection via adversarial training,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.376738Z digest=sha256:ea5184d7ad89f023cd3206654d7dca74ac220c60d4f351f8b18669a9a9f52ee0

Observation f8b30f42-6084-43d9-a7a7-b285d25abaf4 · outbound

This paper cites Towards visually explaining variational autoencoders,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Towards visually explaining variational autoencoders,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.380949Z digest=sha256:8fb5ee814fb41fc4dad8e5c67360e17c98c4e9936c40b5598818dd9e3a94049b

Observation 01fe45ba-9677-4337-a924-733b99486498 · outbound

This paper cites Adversarial 3d convolutional auto- encoder for abnormal event detection in videos,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Adversarial 3d convolutional auto- encoder for abnormal event detection in videos,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.385458Z digest=sha256:a46987a6c0cc376776bbcb8ac9272d71682c6ea93d24ffaea104123c4ec4a437

Observation 04f65337-ad33-4903-bc2f-a8f1bd0396cf · outbound

This paper cites Pull & push: Leveraging differential knowledge distillation for efficient unsupervised anomaly detection and localization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Pull & push: Leveraging differential knowledge distillation for efficient unsupervised anomaly detection and localization,

Reference 31

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raw_fallback, observed 2026-08-15T18:51:48.188294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.389936Z digest=sha256:c536e672178488dedbae71ba56214deb10fe6b3498c7dbd02b26ab577d957736

Observation 95594ba9-da84-4e50-b965-7d42af5d3342 · outbound

This paper cites Logicad: Explainable anomaly detection via vlm-based text feature extraction,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Logicad: Explainable anomaly detection via vlm-based text feature extraction,

Reference 32

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raw_fallback, observed 2026-08-15T18:51:48.173480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.394956Z digest=sha256:9449807f3005a4c57aca95eed6971437e10ddf6cd479ad3aca3d77617d70379f

Observation 73402fe6-14bd-4e7a-b2c5-1daf9066315d · outbound

This paper cites Neural discrete representation learning,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Neural discrete representation learning,

Reference 33

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raw_fallback, observed 2026-08-15T18:51:48.158328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.399532Z digest=sha256:096b23089591858f8ce15b92469f25b8ef216547a8b93b5edd53922b2721864c

Observation a35dbdc9-8571-4c9b-9878-ad52a4b487e1 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection High- resolution image synthesis with latent diffusion models,

Reference 34

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no resolver link, observed 2026-08-15T18:51:47.403902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.403902Z digest=sha256:24eefe3e8f8bde1a5f1dbb182bec35312bfb1d472d1c49f805ee2c92fe67b174

Observation ebe411db-eada-4479-aca0-a5b3117845f8 · outbound

This paper cites Generating diverse structure for image inpainting with hierarchical vq-vae,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Generating diverse structure for image inpainting with hierarchical vq-vae,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.133262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.408271Z digest=sha256:5020264b6fdb5d0f65ae7b59052faee2e695f134caa172f320cddd1ffa542fe0

Observation b8fccbca-7a9b-44ce-8ec1-eb0983c82c2b · outbound

This paper cites Low bit-rate speech coding with vq-vae and a wavenet decoder,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Low bit-rate speech coding with vq-vae and a wavenet decoder,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.118179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.412826Z digest=sha256:987481e87dc7f2fa3217efdd265c689dc8352650be779835f97bf4b9a9dfed3d

Observation 56d50039-317c-47a3-8da3-462a1ff96f50 · outbound

This paper cites Msmc- tts: Multi-stage multi-codebook vq-vae based neural tts,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Msmc- tts: Multi-stage multi-codebook vq-vae based neural tts,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.102939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.417292Z digest=sha256:fc4ba1680c5d2d0e00e36fea2574466205973565fc67a6b2f763691c7f116cc0

Observation 0333b6d4-1787-470e-8236-3fe144a3fe7d · outbound

This paper cites Unsupervised brain imaging 3d anomaly detection and segmentation with transformers,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Unsupervised brain imaging 3d anomaly detection and segmentation with transformers,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.088592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.421895Z digest=sha256:c602c7afc27fe39c9afa312dc481af636471664f98ab719053cf497b2b3cf9ab

Observation 12f8ed77-b3ca-4f73-9388-4e4ddb6ac8a9 · outbound

This paper cites Fast unsupervised brain anomaly detection and segmentation with diffusion models,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Fast unsupervised brain anomaly detection and segmentation with diffusion models,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.073979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.426668Z digest=sha256:2298cd0c45766b2dd7fc396371861fbd94a332b062f2b56a0dcc8104df482e21

Observation 9302b489-0ebb-4109-870a-8011511c6ee3 · outbound

This paper cites Intrusion detection for high-speed railways based on unsupervised anomaly detection models,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Intrusion detection for high-speed railways based on unsupervised anomaly detection models,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.059536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.431236Z digest=sha256:42b666f4925c1a95f0ccd415e536264d9096bf8a9022b567aac0929f0a5d28ae

Observation 34e7ea79-50af-4385-b144-3e3d40440453 · outbound

This paper cites Unified vision-language pre-training for image captioning and vqa,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Unified vision-language pre-training for image captioning and vqa,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.043953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.435719Z digest=sha256:cd3dfdd41a6571113e1276e3a08f881ac98ce39f057c045f72e435e4c2c902ec

Observation 5dafee77-e848-452c-b863-bf110baf4198 · outbound

This paper cites Label2label: A language modeling framework for multi-attribute learning,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Label2label: A language modeling framework for multi-attribute learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.027461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.440162Z digest=sha256:da61f35f125d8f999b38660dfb28b65a4bfc36e0df10efb6b0bbe6da4ed39e2a

Observation b0312471-c967-4366-bd0b-3a2d2f390244 · outbound

This paper cites Clip4caption: Clip for video caption,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Clip4caption: Clip for video caption,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:48.011655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.444789Z digest=sha256:734e8a3e4a2e9051003f810dcc01e2e4e34a87f6eae7776f4f5174c712ac1f26

Observation b662630e-dac5-43ea-b745-dc18fbd9b836 · outbound

This paper cites Multimodal local-global attention network for affective video content analysis,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Multimodal local-global attention network for affective video content analysis,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.996516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.449785Z digest=sha256:5e6420f0aab7b83cbaf94c7224487ab8127fb9b9ead853761838aab82e377c32

Observation 76678a1b-9680-4720-a834-c094ad6d5339 · outbound

This paper cites Virtex: Learning visual representations from textual annotations,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Virtex: Learning visual representations from textual annotations,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.981318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.454129Z digest=sha256:ae76cefea5f428d8fcb7528f783b2f3d003345fd0135d18ffb7065dd773cf0bb

Observation 3f4771d4-23ae-4001-a176-79dc9d8de0ce · outbound

This paper cites A simple baseline for open-vocabulary semantic segmentation with pre- trained vision-language model,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection A simple baseline for open-vocabulary semantic segmentation with pre- trained vision-language model,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.966780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.458944Z digest=sha256:deae958eaed5d2f7025e33b09b8523b5c4e8f873df25895d09b9224ee41e7a07

Observation 5d980f3e-72a3-4898-bce1-77e329b574b5 · outbound

This paper cites X-clip: End- to-end multi-grained contrastive learning for video-text retrieval,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection X-clip: End- to-end multi-grained contrastive learning for video-text retrieval,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T18:51:47.463632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.463632Z digest=sha256:600f2beb5d138660c7830d76f6fdb0a05f6b3db8880201bf6afd6b8783c3d35f

Observation 8663e807-6e25-47e7-8c80-8a834c6c3dfd · outbound

This paper cites Hit: Hier- archical transformer with momentum contrast for video-text retrieval,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Hit: Hier- archical transformer with momentum contrast for video-text retrieval,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.941281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.467996Z digest=sha256:7863e4b0b93a63a28be9f9c4046942137b1c364bae99a1739d38ed4dd83b52cb

Observation 3bba8fd5-c2a1-4655-a9c9-e30ce919f66d · outbound

This paper cites CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T18:51:47.472317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.472317Z digest=sha256:80b1421ed80e13532e8cab926df3f41e2017e14f25f43b9edef1532ac6c3c145

Observation f3c41eee-88d7-4d20-aeaa-a81b36e2e056 · outbound

This paper cites Long movie clip classification with state-space video models,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Long movie clip classification with state-space video models,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.924586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.476902Z digest=sha256:cdfdd5853a2cdb187f23044e5aa51a83e853c30501e4d6a5b5cbc208135286c8

Observation f384c9e6-2e84-42f7-b230-c1545d5b4414 · outbound

This paper cites Cris: Clip- driven referring image segmentation,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Cris: Clip- driven referring image segmentation,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.909777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.481902Z digest=sha256:ea9dcdf05f098519137d607fc70f6ee985d8929fcddfd2a502fd4fd3c1fc3d89

Observation 102400ce-adb8-4231-b2d8-0574d43992e2 · outbound

This paper cites Per-clip video object segmentation,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Per-clip video object segmentation,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.894733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.487286Z digest=sha256:afcfa8811fe54334db10129c2cf91ba43c7128cc3009dd4f83a00b070feb76e5

Observation 365db461-9a3b-423a-a16e-97e213343ea4 · outbound

This paper cites An elementary proof of a theorem of johnson and lindenstrauss,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection An elementary proof of a theorem of johnson and lindenstrauss,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.879469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.491652Z digest=sha256:3f3d2ef9c9e898645e681a3567ee2a42b7e77c4eeb29d3e05a08910a48172fa1

Observation 4753964c-563f-4c8f-bbbc-1a2bd39ee383 · outbound

This paper cites Steger, M.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Steger, M

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.863596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.495842Z digest=sha256:f9e68169c303f69707997c5e9f05dc2044752249c7992af14ebc9e6bc2de10dd

Observation 6a906e27-732a-4bd3-81f7-10f8999d2740 · outbound

This paper cites f-anogan: Fast unsupervised anomaly detection with generative adversarial networks,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection f-anogan: Fast unsupervised anomaly detection with generative adversarial networks,

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T18:51:47.500178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.500178Z digest=sha256:22e2ccebd5c08f8842cc93b53e9f121d45685e7cb78bbac8f4ad100c175abc53

Observation be79496f-be09-4ec0-b03b-513a7ab6b7df · outbound

This paper cites Variational autoencoder based anomaly detection using reconstruction probability,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Variational autoencoder based anomaly detection using reconstruction probability,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.838946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.504793Z digest=sha256:1f71023eed4157b244968cc98faa0ee93f2aadb6ccb01d363cee5f3c0d3157b3

Observation dea6fe65-dc27-4d71-b2dc-c3b1e705daa9 · outbound

This paper cites Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T18:51:47.509239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.509239Z digest=sha256:0ad186c636e5d7e7287ddacf3c56288fad2e196030d333958d86e758a2d18842

Observation ba16046c-f7e3-49e5-809f-14872980a0d8 · outbound

This paper cites Padim: a patch dis- tribution modeling framework for anomaly detection and localization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Padim: a patch dis- tribution modeling framework for anomaly detection and localization,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.823871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.514123Z digest=sha256:e8d56eaa3b23d442496664758483c78bf51a859b1a83bac09d0dd384fa42be63

Observation 622e9d78-4b05-4426-916f-c144758bf863 · outbound

This paper cites Vt- adl: A vision transformer network for image anomaly detection and localization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Vt- adl: A vision transformer network for image anomaly detection and localization,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.809222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.518568Z digest=sha256:4916cebc514047bf4ba60e5f767240fb074aece76c0ea56945488e3678a8bdc5

Observation e4f78efe-d689-4bf4-93d7-d464f67f1923 · outbound

This paper cites Deep residual learning for image recognition,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Deep residual learning for image recognition,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.793184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.523719Z digest=sha256:5b30f2bb29aff7ca9f1e84db4595f7aeb9421e404a2441d331f421d16d9fd5df

Observation 1d15ff62-a61a-4d6e-99b1-fb2779f8c022 · outbound

This paper cites Aggregated resid- ual transformations for deep neural networks,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Aggregated resid- ual transformations for deep neural networks,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.777406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.528065Z digest=sha256:201d392c16631efee6c04b3659a68b89bf8f665f066608c0d92002b39ceec0a4

Observation 6df7d3b9-e991-4658-b026-d447423b5cc4 · outbound

This paper cites Uformer: A general u-shaped transformer for image restoration,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Uformer: A general u-shaped transformer for image restoration,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.760105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.532395Z digest=sha256:f7314bc1baf7dd73962cd3b11ed057840d5af0138d731d4b542077183594056c

Observation 959ea355-e177-469c-813e-f0cb1e23bdef · outbound

This paper cites Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:51:47.621609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.536814Z digest=sha256:0dc4fd1c32103b85e2329c131c42114e28ed4f822448140457647bdb9c0fa507

Observation 69ee84fc-8ffb-45ca-96f7-1d0cbb75b176 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Adam: A Method for Stochastic Optimization

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-15T18:51:47.541575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:51:47.541575Z digest=sha256:b20b1e0a5c5bb0513744174ebf784ca9ec6e38f94b37d566123571f3205741f5

Observation 6e0d853f-185c-4a83-979e-5f2306b6ae67 · outbound

This paper cites Patch svdd: Patch-level svdd for anomaly detection and segmentation,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Patch svdd: Patch-level svdd for anomaly detection and segmentation,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.743212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.546955Z digest=sha256:eaf8bc7033a4ddba014d96bcec796f86935157912f0738645f859bfcc799767e

Observation 5c262043-2be3-4ac9-b320-6f2135620372 · outbound

This paper cites Draem-a discriminatively trained reconstruction embedding for surface anomaly detection,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Draem-a discriminatively trained reconstruction embedding for surface anomaly detection,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.728006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.551320Z digest=sha256:342d8835472ad3c8c9b32c22a448f9bb0e6566146253edba5b7a37952872366a

Observation 104dbd85-0711-49cf-867f-aba4a7acad35 · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Cutpaste: Self-supervised learning for anomaly detection and localization,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.713024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.555769Z digest=sha256:7e4a59cb042825f214b483d19ed8407fe70324c27be12a0308cc9a50e2350b04

Observation 988775d5-b866-44ce-b996-7bd762f38470 · outbound

This paper cites Same same but differnet: Semi-supervised defect detection with normalizing flows,.

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection Same same but differnet: Semi-supervised defect detection with normalizing flows,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:51:47.698499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:51:47.560314Z digest=sha256:1c9f7e66fc0db79e6d5d17889eea993ccb41406f52bcf31386f80242cc0aa7ba

Pith citing papers

No inbound Pith citation observations are available.