Paper Citation Record · LEDGER

HomographyAD: Deep Anomaly Detection Using Self Homography Learning

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.08784.

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

pith.paper-citation-record.v1
2506.08784 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:05:37.673869Z

measured 35 of 35 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

35 of 35 outbound references displayed

verified exact1
verified fuzzy26
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0642ec71-0809-4638-af8a-c78c570e969b · outbound

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

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Ganomaly: Semi- supervised anomaly detection via adversarial training

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.938579Z

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.

Observation ff9868b1-05b9-42cb-abcc-4ddb33484413 · outbound

This paper cites Image based quality inspection in smart manufacturing systems: A literature review.Procedia CIRP, 103:262–267, 2021.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Image based quality inspection in smart manufacturing systems: A literature review.Procedia CIRP, 103:262–267, 2021

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.775909Z

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.

Observation 5eab584f-9b83-419f-8dc3-91d6692b8a15 · outbound

This paper cites Lucas-kanade 20 years on: A unifying frame- work.International journal of computer vision, 56(3):221–255, 2004.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Lucas-kanade 20 years on: A unifying frame- work.International journal of computer vision, 56(3):221–255, 2004

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.679935Z

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.

Observation b847da18-8e1f-44cb-8c07-6e97f3efbef9 · outbound

This paper cites Deep Nearest Neighbor Anomaly Detection.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep Nearest Neighbor Anomaly Detection

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:34.668810Z

Source-reported events for the cited work

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Observation ad490edc-9e1f-4ec8-8939-6a3af101b36c · outbound

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

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.668283Z

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.

Observation a292634a-4737-4c56-a329-a5860b757881 · outbound

This paper cites Clkn: Cascaded lucas- kanade networks for image alignment.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Clkn: Cascaded lucas- kanade networks for image alignment

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.648054Z

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.

Observation 935eaeda-def4-4407-b4b1-553d8cdc7f23 · outbound

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

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Sub-Image Anomaly Detection with Deep Pyramid Correspondences

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:35.053876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cda040f0-4d01-4d6e-ad6e-0e8670716b8b · outbound

This paper cites Padim: a patch distribution modeling framework for anomaly detection and lo- calization.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Padim: a patch distribution modeling framework for anomaly detection and lo- calization

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.636325Z

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.

Observation fa210436-4a52-491b-b304-9bed30fe2855 · outbound

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

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Imagenet: A large-scale hierarchical image database

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:35.330728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd21d5a0-e41d-4c94-b69f-67ff2bca894d · outbound

This paper cites Deep Image Homography Estimation.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep Image Homography Estimation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:35.444759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 514c0ae5-0899-4e6d-ac93-053975dce884 · outbound

This paper cites Homography estimation from image pairs with hierarchical convolutional networks.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Homography estimation from image pairs with hierarchical convolutional networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.621382Z

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.

Observation 544c26a0-c0ea-495f-977e-7f2b516cd8d2 · outbound

This paper cites ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:35.769910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66b67abd-841e-46d6-a4fc-f5754ad180e2 · outbound

This paper cites Unsupervised Representation Learning by Predicting Image Rotations.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Unsupervised Representation Learning by Predicting Image Rotations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:35.918752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca8d7229-975d-46f5-91a8-f68bba0a8cae · outbound

This paper cites Deep anomaly detection using geometric trans- formations.Advances in neural information processing systems, 31, 2018.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep anomaly detection using geometric trans- formations.Advances in neural information processing systems, 31, 2018

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.613119Z

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.

Observation 84ce5357-5da4-4757-929d-fd305c05ce9d · outbound

This paper cites Generative adver- sarial nets.Advances in neural information processing systems, 27, 2014.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Generative adver- sarial nets.Advances in neural information processing systems, 27, 2014

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.604341Z

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.

Observation b51f5d8f-6907-47f0-96bc-4560484c142c · outbound

This paper cites Deep residual learn- ing for image recognition.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep residual learn- ing for image recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.595167Z

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.

Observation 3d873e35-0ce4-4500-8f91-76852d458801 · outbound

This paper cites Using self- supervised learning can improve model robustness and uncertainty.Advances in neural information processing systems, 32, 2019.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Using self- supervised learning can improve model robustness and uncertainty.Advances in neural information processing systems, 32, 2019

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.585960Z

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.

Observation 1c8660eb-8350-425f-a0f2-0f9d831fc27e · outbound

This paper cites Surface defect saliency of magnetic tile.The Visual Computer, 36(1):85–96, 2020.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Surface defect saliency of magnetic tile.The Visual Computer, 36(1):85–96, 2020

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.574065Z

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.

Observation a3e4f0dc-c5cb-4d44-b334-93a9803e1c73 · outbound

This paper cites Perceptual loss for robust unsupervised homography estimation.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Perceptual loss for robust unsupervised homography estimation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.565551Z

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.

Observation bdc52ba0-e389-4b57-9962-c9a92c591de6 · outbound

This paper cites Distinctive image features from scale-invariant keypoints.Inter- national journal of computer vision, 60(2):91–110, 2004.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Distinctive image features from scale-invariant keypoints.Inter- national journal of computer vision, 60(2):91–110, 2004

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.556798Z

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.

Observation dec2dbba-fb18-40e8-9505-f609ab060d61 · outbound

This paper cites On the generalized distance in statistics.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning On the generalized distance in statistics

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.547535Z

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.

Observation aa1f35a9-df35-4ba4-b0a1-ad867c00c930 · outbound

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

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Vt-adl: A vision transformer network for image anomaly detection and localization

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.538963Z

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.

Observation 73165335-fe01-45d3-be05-34e45fce0bdf · outbound

This paper cites Unsupervised deep homography: A fast and robust homography estimation model.IEEE Robotics and Automation Letters, 3(3):2346–2353, 2018.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Unsupervised deep homography: A fast and robust homography estimation model.IEEE Robotics and Automation Letters, 3(3):2346–2353, 2018

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.529409Z

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.

Observation 0b60211d-42c5-401c-9b57-21a7dda5337c · outbound

This paper cites an unresolved cited work.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:39.518627Z

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.

Observation 26af7b95-f172-4364-85ee-195a71c8461e · outbound

This paper cites Deep learning for anomaly detection: A review.ACM Computing Surveys (CSUR), 54(2):1–38, 2021.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep learning for anomaly detection: A review.ACM Computing Surveys (CSUR), 54(2):1–38, 2021

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:39.263630Z

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.

Observation b0979a5a-4ef5-4e5e-b25e-c6744b34d81a · outbound

This paper cites Modeling the distribution of normal data in pre-trained deep features for anomaly detection.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Modeling the distribution of normal data in pre-trained deep features for anomaly detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.969238Z

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.

Observation 6944a0cf-8239-49af-9cab-99b24adf9736 · outbound

This paper cites Towards total recall in industrial anomaly detection.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Towards total recall in industrial anomaly detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.744462Z

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.

Observation 36a98c57-7273-48cf-89ea-3d4ef3e9c5c0 · outbound

This paper cites Orb: An ef- ficient alternative to sift or surf.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Orb: An ef- ficient alternative to sift or surf

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.620183Z

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.

Observation c25fcaae-a099-4093-b5cd-491ed2b82394 · outbound

This paper cites Deep one-class classification.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Deep one-class classification

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.478911Z

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.

Observation 58f6ec61-22b6-4b64-9380-6f82b19b50fc · outbound

This paper cites Unsupervised anomaly detection with generative ad- versarial networks to guide marker discovery.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Unsupervised anomaly detection with generative ad- versarial networks to guide marker discovery

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.347949Z

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.

Observation 1fb262a5-de9b-4fe9-a242-a12c63719b9a · outbound

This paper cites Learning and Evaluating Representations for Deep One-class Classification.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Learning and Evaluating Representations for Deep One-class Classification

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:05:37.794037Z

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.

Observation a4f494a5-2fa5-41d8-bda6-415f3cdedad3 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolu- tional neural networks.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Efficientnet: Rethinking model scaling for convolu- tional neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.222523Z

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.

Observation 162ec43b-49bc-4ecb-8405-9c03b8dbaae7 · outbound

This paper cites Wide Residual Networks.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Wide Residual Networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.574394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 879439a1-0c11-4ca4-af8d-2eba50ee5aed · outbound

This paper cites Rethinking planar homography estimation using perspective fields.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Rethinking planar homography estimation using perspective fields

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.103320Z

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.

Observation fd328788-9520-40d6-b1a5-0d93df1268f9 · outbound

This paper cites Content-aware unsupervised deep homography estimation.

HomographyAD: Deep Anomaly Detection Using Self Homography Learning Content-aware unsupervised deep homography estimation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:37.967695Z

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.

Pith citing papers

No inbound Pith citation observations are available.