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Paper Citation Record · LEDGER

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns

As of 16 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:1908.09327.

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

pith.paper-citation-record.v1
1908.09327 v3

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:19:34.285727Z

measured 38 of 38 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

38 of 38 outbound references displayed

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  • verified fuzzy29
  • unresolved9
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 868bb443-7091-4a52-915d-4503558bab90 · outbound

This paper cites An improved deep learning architecture for person re-identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns An improved deep learning architecture for person re-identification

Reference 1

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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 ad24b906-6df4-4202-8262-6608b9fd5919 · outbound

This paper cites Synthesizing Robust Adversarial Examples.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Synthesizing Robust Adversarial Examples

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4fa711a5-9d29-498a-be38-00e0af87deda · outbound

This paper cites Towards evaluating the robustness of neural networks.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Towards evaluating the robustness of neural networks

Reference 3

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Source-reported events for the cited work

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

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Observation 1371fc2c-0c35-469c-bdf8-c16a0763d264 · outbound

This paper cites Deep ranking for person re-identification via joint representa- tion learning.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deep ranking for person re-identification via joint representa- tion learning

Reference 4

Resolution
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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 9a627a82-6057-45d2-a007-edfa0b823200 · outbound

This paper cites A multi-task deep network for person re- identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns A multi-task deep network for person re- identification

Reference 5

Resolution
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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 36d17007-e218-43ef-8bff-ecd52cdfa9de · outbound

This paper cites Person re-identification by multi-channel parts-based cnn with improved triplet loss function.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Person re-identification by multi-channel parts-based cnn with improved triplet loss function

Reference 6

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Source-reported events for the cited work

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Observation 3ea8435e-ef70-4745-8c04-705c5d119452 · outbound

This paper cites Deep feature learning with relative distance comparison for person re-identification.Pattern Recognition, 48(10):2993–3003, 2015.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deep feature learning with relative distance comparison for person re-identification.Pattern Recognition, 48(10):2993–3003, 2015

Reference 7

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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 13d01826-d98b-4909-b17f-da0b345f4846 · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Robust physical-world attacks on deep learning visual classification

Reference 8

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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 950bf45e-3c2f-4e98-b402-d25963cea6b5 · outbound

This paper cites The re-identification challenge.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns The re-identification challenge

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 9e061aa0-b1db-45ad-a53e-236937eb83ee · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Explaining and Harnessing Adversarial Examples

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ababaec7-0ecf-4525-b51d-2e57b490885e · outbound

This paper cites Adversarial Perturbations Against Deep Neural Networks for Malware Classification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Adversarial Perturbations Against Deep Neural Networks for Malware Classification

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 76d5a4f0-096e-478f-87a6-5661c0b13a13 · outbound

This paper cites Deep residual learning for image recognition.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deep residual learning for image recognition

Reference 12

Resolution
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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 ef1b9e60-9488-46cd-8003-67fb13ff9239 · outbound

This paper cites Adversarial exam- ples for generative models.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Adversarial exam- ples for generative models

Reference 13

Resolution
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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 f4fbebdf-1833-4c70-bf0f-5b66487d88c0 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Imagenet classification with deep convolutional neural net- works

Reference 14

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verified fuzzy
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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 bfa0ffbd-3462-47d8-8488-282f3b22dfe2 · outbound

This paper cites Adversarial examples in the physical world.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Adversarial examples in the physical world

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5cc5e921-9380-4234-97f7-898639663b2d · outbound

This paper cites Feature cross-substitution in adversarial classification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Feature cross-substitution in adversarial classification

Reference 16

Resolution
verified fuzzy
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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 db51c017-0e10-4b21-bfb2-5950c19872df · outbound

This paper cites Scalable optimization of randomized operational decisions in adversarial classifica- tion settings.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Scalable optimization of randomized operational decisions in adversarial classifica- tion settings

Reference 17

Resolution
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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 ebf4a3da-f331-42c6-a143-e0505ef50c8a · outbound

This paper cites Deep- reid: Deep filter pairing neural network for person re- identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deep- reid: Deep filter pairing neural network for person re- identification

Reference 18

Resolution
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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 ba064ed8-0e75-463f-bef0-ed35d0c455c6 · outbound

This paper cites Delving into Transferable Adversarial Examples and Black-box Attacks.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Delving into Transferable Adversarial Examples and Black-box Attacks

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e8828b48-b3c3-4277-ba36-5adeed5c10cd · outbound

This paper cites Multi- camera activity correlation analysis.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Multi- camera activity correlation analysis

Reference 20

Resolution
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raw_fallback, observed 2026-08-14T11:19:34.716309Z

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 ab63ed06-8293-406d-bbb6-01b74e2286e6 · outbound

This paper cites Understanding deep image representations by inverting them.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Understanding deep image representations by inverting them

Reference 21

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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 c9c2b32c-bfe7-440f-802e-4166646942e8 · outbound

This paper cites Deepfool: a simple and accurate method to fool deep neural networks.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deepfool: a simple and accurate method to fool deep neural networks

Reference 22

Resolution
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raw_fallback, observed 2026-08-14T11:19:34.685697Z

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 92a26411-4f5e-4805-91cd-f790e9f18fc5 · outbound

This paper cites Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Reference 23

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation acfb905a-2ef8-49fb-8292-6ab36e85c528 · outbound

This paper cites The limitations of deep learning in adversarial settings.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns The limitations of deep learning in adversarial settings

Reference 24

Resolution
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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 a34fb749-7f89-487c-9c4f-a47871d8d9da · outbound

This paper cites Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.653940Z

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 210ed392-7c4f-44c9-8818-83226c37a41a · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 26

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no resolver link, observed 2026-08-14T11:19:34.225922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7992e4e4-cfda-4448-87cc-431fc2a7e052 · outbound

This paper cites Going deeper with convolutions.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Going deeper with convolutions

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.637711Z

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 6d014810-2963-4065-bf4c-3c9b57fca6e8 · outbound

This paper cites Intriguing properties of neural networks.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Intriguing properties of neural networks

Reference 28

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no resolver link, observed 2026-08-14T11:19:34.236407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 11322698-0625-4d1f-9165-214f54c7ed3a · outbound

This paper cites Joint learning of single-image and cross- image representations for person re-identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Joint learning of single-image and cross- image representations for person re-identification

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.621659Z

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 ee481e28-cd68-4340-997c-b5b5df5c2883 · outbound

This paper cites Intelligent multi-camera video surveil- lance: A review.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Intelligent multi-camera video surveil- lance: A review

Reference 30

Resolution
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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 bffc831a-e0c3-44b8-a281-a963b63750d0 · outbound

This paper cites Learning deep feature representations with domain guided dropout for person re-identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Learning deep feature representations with domain guided dropout for person re-identification

Reference 31

Resolution
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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.

source=pdf_text observed=2026-08-14T11:19:34.250912Z digest=sha256:0934715a5b165012daf84c6edcfa02118c4c17a4dc34722cf54d61db52b4d536

Observation ea85a32f-1177-4809-a728-74f343ccd01d · outbound

This paper cites Deep metric learning for person re-identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Deep metric learning for person re-identification

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.565883Z

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 c25dd5b6-51e9-4a56-b9d4-758f12d77da8 · outbound

This paper cites Harry potter’s marauder’s map: Localizing and tracking multiple persons-of-interest by nonnegative discretization.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Harry potter’s marauder’s map: Localizing and tracking multiple persons-of-interest by nonnegative discretization

Reference 33

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-08-14T11:19:34.260550Z digest=sha256:074beb172b9d944ae5cc302cc41bcbad724a0e6a93cf36a9e11c9ea34f9dcd79

Observation 2b6fe0bd-79d9-49de-a36f-fd436a2c1b29 · outbound

This paper cites Age progres- sion/regression by conditional adversarial autoencoder.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Age progres- sion/regression by conditional adversarial autoencoder

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.526531Z

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=2026-08-14T11:19:34.265643Z digest=sha256:b1810921c3e74d6e42fbfc8af0c6a6d9189cc209725caf99a8f1225a3f1b8e1e

Observation 13aabb1d-5c0c-4bb4-a485-5c5c2eb77eb7 · outbound

This paper cites Im- age super-resolution by neural texture transfer.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Im- age super-resolution by neural texture transfer

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.507791Z

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=2026-08-14T11:19:34.271192Z digest=sha256:ae7fa0728ad23318939e9d8e514cf5225cba9ef42e25a27403cf913596a109f0

Observation ac01f514-478d-42ab-8601-29a1d331ad1e · outbound

This paper cites Person Re-identification: Past, Present and Future.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Person Re-identification: Past, Present and Future

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:34.275737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:34.275737Z digest=sha256:8e61c6afdc64a6f28bb703945756fec1e6f5c7bc343f26d206b3740974160b8f

Observation 10613c77-578c-49e8-ae44-d8ca64dddca9 · outbound

This paper cites A discrimi- natively learned cnn embedding for person reidentification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns A discrimi- natively learned cnn embedding for person reidentification

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.490333Z

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=2026-08-14T11:19:34.280910Z digest=sha256:c2fb13d44fae2274cccf07708d457271eea3249a7b0b109526ff49bc6ffd0212

Observation 5ff2eaa4-ec0f-415c-b741-379ac8461042 · outbound

This paper cites Camera style adaptation for person re- identification.

advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Camera style adaptation for person re- identification

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:34.471562Z

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=2026-08-14T11:19:34.285727Z digest=sha256:1048c84e71fd3d143598e845376b408295524e8827e1d23facada9253beef002

Pith citing papers

No inbound Pith citation observations are available.