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Paper Citation Record · LEDGER

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification

As of 19 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:1908.10486.

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

pith.paper-citation-record.v1
1908.10486 v3

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:48:08.751167Z

measured 57 of 57 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

57 of 57 outbound references displayed

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  • unresolved5
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f6065dd-c831-49e8-8f77-099f871c4556 · outbound

This paper cites Camera networks: The acquisition and analysis of videos over wide areas,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Camera networks: The acquisition and analysis of videos over wide areas,

Reference 1

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Source-reported events for the cited work

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

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Observation 73004271-1409-40c9-ae28-83e26dc37f0a · outbound

This paper cites Deep Learning for Person Re-identification: A Survey and Outlook.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Deep Learning for Person Re-identification: A Survey and Outlook

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b6622621-b7fd-4491-936d-0bada183f3d2 · outbound

This paper cites Spatial-temporal attention-aware learning for video-based person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Spatial-temporal attention-aware learning for video-based person re-identification,

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 29768b7c-23ea-47ad-9164-2ade92c9a48c · outbound

This paper cites Learning discriminative aggregation network for video-based face recognition and person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Learning discriminative aggregation network for video-based face recognition and person re-identification,

Reference 4

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

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Observation ba1550e5-c57e-4468-a444-4dfdeadcb05d · outbound

This paper cites Robust anchor embedding for unsupervised video person re-identification in the wild,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Robust anchor embedding for unsupervised video person re-identification in the wild,

Reference 5

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Source-reported events for the cited work

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Observation 6e1580e7-eacd-4005-979c-987843b5cf35 · outbound

This paper cites Dynamic graph co- matching for unsupervised video-based person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Dynamic graph co- matching for unsupervised video-based person re-identification,

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 63d4b624-bad6-485f-8eff-39173d564dab · outbound

This paper cites Global-local temporal representations for video person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Global-local temporal representations for video person re-identification,

Reference 7

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Source-reported events for the cited work

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Observation 6f4f66ec-377e-432c-ba4d-c208fac4df01 · outbound

This paper cites Video-based person re-identification via self-paced learning and deep reinforcement learning framework,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Video-based person re-identification via self-paced learning and deep reinforcement learning framework,

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 07f8236c-e731-4317-82a4-9397e61a1e0f · outbound

This paper cites Purifynet: A robust person re-identification model with noisy labels,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Purifynet: A robust person re-identification model with noisy labels,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 97557789-6ad3-426f-8a03-3ee6ddbeecf7 · outbound

This paper cites Deep association learning for unsu- pervised video person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Deep association learning for unsu- pervised video person re-identification,

Reference 10

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Source-reported events for the cited work

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Observation 4a313f77-6563-42ee-b0f4-168b8312b2ea · outbound

This paper cites Hierarchical temporal modeling with mutual distance matching for video based person re- identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Hierarchical temporal modeling with mutual distance matching for video based person re- identification,

Reference 11

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Source-reported events for the cited work

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Observation 59e72c0b-d5b5-4684-acb8-1793ac19fe45 · outbound

This paper cites Dynamic label graph matching for unsupervised video re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Dynamic label graph matching for unsupervised video re-identification,

Reference 12

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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.

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Observation 5ed01c2e-7841-4315-93f4-1107518a66ae · outbound

This paper cites Video-based person re- identification using unsupervised tracklet matching,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Video-based person re- identification using unsupervised tracklet matching,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 67e5867f-d5e4-4153-b8ec-cfd81bb97f36 · outbound

This paper cites Tracklet self-supervised learning for un- supervised person re-identification.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Tracklet self-supervised learning for un- supervised person re-identification

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 900d6941-eff3-47b2-afb7-dd27c1c07791 · outbound

This paper cites Cross-modality person re- identification via modality-aware collaborative ensemble learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Cross-modality person re- identification via modality-aware collaborative ensemble learning,

Reference 15

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Source-reported events for the cited work

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

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Observation 826ea762-abfa-4774-ae29-51ba83582c96 · outbound

This paper cites Learning Person Re-identification Models from Videos with Weak Supervision.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Learning Person Re-identification Models from Videos with Weak Supervision

Reference 16

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 54c02d6a-b677-4397-a000-cc7b9847826b · outbound

This paper cites Augmentation invariant and instance spreading feature for softmax embedding,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Augmentation invariant and instance spreading feature for softmax embedding,

Reference 17

Resolution
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Source-reported events for the cited work

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

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Observation 7a4369b9-17c0-42df-aa45-4ad961ffdd91 · outbound

This paper cites A bottom-up clustering approach to unsupervised person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification A bottom-up clustering approach to unsupervised person re-identification,

Reference 18

Resolution
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Source-reported events for the cited work

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Observation e3a7a189-d921-4bd6-95a1-2085d8291eac · outbound

This paper cites Unsupervised person re- identification: Clustering and fine-tuning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised person re- identification: Clustering and fine-tuning,

Reference 19

Resolution
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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.

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Observation 98c9314a-8312-47d3-8fdd-9e6028cfcfb9 · outbound

This paper cites Unsupervised person re-identification by soft multilabel learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised person re-identification by soft multilabel learning,

Reference 20

Resolution
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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.

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Observation 2520fb30-3ea8-40b2-8459-5e830950281c · outbound

This paper cites Self- similarity grouping: A simple unsupervised cross domain adaptation approach for person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Self- similarity grouping: A simple unsupervised cross domain adaptation approach for person re-identification,

Reference 21

Resolution
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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.

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Observation a931cc68-7bef-41da-b9f4-2eb6c4bf1c14 · outbound

This paper cites Self-training with progressive augmentation for unsupervised cross-domain person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Self-training with progressive augmentation for unsupervised cross-domain person re-identification,

Reference 22

Resolution
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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.

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Observation ba5cedb0-732a-4ce7-b4dd-59d67d07cfdc · outbound

This paper cites Prism: Person reidentification via struc- tured matching,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Prism: Person reidentification via struc- tured matching,

Reference 23

Resolution
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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.

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Observation e40dc1c9-1bb5-4bc4-beee-d8ffba7a8c83 · outbound

This paper cites Fully unsupervised learning of camera link models for tracking humans across nonoverlapping cameras,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Fully unsupervised learning of camera link models for tracking humans across nonoverlapping cameras,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 087209de-1551-40b6-8b51-96b129bdaafa · outbound

This paper cites Unsupervised person re-identification via softened similarity learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised person re-identification via softened similarity learning,

Reference 25

Resolution
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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.

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Observation 048a0a59-e8d3-4f8f-8f5d-b5660cb50955 · outbound

This paper cites Consistent-aware deep learn- ing for person re-identification in a camera network,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Consistent-aware deep learn- ing for person re-identification in a camera network,

Reference 26

Resolution
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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.

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Observation 0ab7eddd-fbf9-4684-84ed-bb5aa6e787f8 · outbound

This paper cites Consistent re- identification in a camera network,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Consistent re- identification in a camera network,

Reference 27

Resolution
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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.

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Observation 7384333a-0680-4477-84cc-f516682426f1 · outbound

This paper cites Network consistent data association,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Network consistent data association,

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation ed24a63e-5376-4b30-899c-1c24e6bb588d · outbound

This paper cites Efficient parameter-free clustering using first neighbor relations,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Efficient parameter-free clustering using first neighbor relations,

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 5e158d7d-48f5-4855-9475-bf289870be72 · outbound

This paper cites Unsupervised person re-identification via cross-camera similarity exploration,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised person re-identification via cross-camera similarity exploration,

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation ef74b818-2fa9-43ab-a825-22fd29e2434c · outbound

This paper cites Joint detection and identification feature learning for person search,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Joint detection and identification feature learning for person search,

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.614687Z digest=sha256:891f3d540b1109f7cfbbd164abe2b6901d3874ebcf6b24f6c00cae4478a2b384

Observation 5a308c86-6f67-47cc-89c7-a35ed2666bac · outbound

This paper cites Stepwise metric promotion for unsu- pervised video person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Stepwise metric promotion for unsu- pervised video person re-identification,

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 9bc329d2-6ac5-4126-89ab-8c9b74540531 · outbound

This paper cites Unsupervised person re-identification by deep learning tracklet association,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised person re-identification by deep learning tracklet association,

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 2026-08-19T06:32:44.657259+00:00.

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Observation dbf7b9b6-dc09-48f5-8c99-9f4ba02c5cbe · outbound

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

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Camera style adaptation for person re-identification,

Reference 34

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:48:08.629422Z digest=sha256:fd856511e0d952dc0b47387ec4cbc56e5c2ed0e80574ccc0e27c175b6ee0710d

Observation 49f58ca2-88ef-4e40-9d40-6e3e11bbda4e · outbound

This paper cites Image- image domain adaptation with preserved self-similarity and domain- dissimilarity for person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Image- image domain adaptation with preserved self-similarity and domain- dissimilarity for person re-identification,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.213579Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.634255Z digest=sha256:8e38428d8a89f1e71ccb1adab5333f8b92ffb37272a69bdccb92f761acb42f48

Observation b0b5df9a-d6dd-4c42-a3a0-81a5ece7096f · outbound

This paper cites Shape matching and object recognition using low distortion correspondences,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Shape matching and object recognition using low distortion correspondences,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.194353Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.639473Z digest=sha256:e8b00345dcadad8679fc19ae5905af3c5c72f9a77a5109ae866357023c1743fe

Observation a62065f6-6780-42d6-b882-4288a5e6626d · outbound

This paper cites Multi-graph matching via affinity optimization with graduated consistency regulariza- tion,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Multi-graph matching via affinity optimization with graduated consistency regulariza- tion,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.177429Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.644209Z digest=sha256:7989bd2fa1fa984eaec1eeebe2ed24763678a722381af3e384b0bee345683a5b

Observation 9adbe457-b7b1-4792-9ab8-f538ec8d7e37 · outbound

This paper cites Pairwise matching through max-weight bipartite belief propagation,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Pairwise matching through max-weight bipartite belief propagation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.161147Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.648961Z digest=sha256:64a3989aa070391a736ba1ef0b6b270208aee20641f332431585b96288e499fe

Observation 31be9c4d-bdf8-4c52-8ce0-d057d252e291 · outbound

This paper cites Unsupervised graph association for person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised graph association for person re-identification,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.143558Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.654045Z digest=sha256:032e3d515e304d3bbbd0c5ea40c19e44677e9c8ae18dcba6296704dc3c547461

Observation 3a6d2354-7fdf-4fde-ac77-bedea5e26e54 · outbound

This paper cites Exploiting transitivity for learning person re-identification models on a budget,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Exploiting transitivity for learning person re-identification models on a budget,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.125741Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.659388Z digest=sha256:cea26997b47e0577ba6cd6a61e628a0ba50f4096f1f4ac897d696b14d4fe9f82

Observation af45dca6-733c-477e-ad58-aadcf598f12a · outbound

This paper cites The hungarian method for the assignment problem,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification The hungarian method for the assignment problem,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-14T10:48:08.664605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:48:08.664605Z digest=sha256:436d4225e06a6041ce88d21e1d67a2eb869a6676f7adc3b27401934f61d34a19

Observation 262bd9ca-9af3-4926-9434-06da81a80def · outbound

This paper cites Efficient psd constrained asymmetric metric learning for person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Efficient psd constrained asymmetric metric learning for person re-identification,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.098629Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.670008Z digest=sha256:8de777caddac3e0761ea461f2d7c24fa0ad6e94af232acd0d932fb4f36f238b7

Observation 162032f9-021b-4c77-adcd-b8d1011f4198 · outbound

This paper cites On the convergence of graph matching: Graduated assignment revisited,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification On the convergence of graph matching: Graduated assignment revisited,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.080948Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.678556Z digest=sha256:bec9480b114929c0438e488d58e2699e0a1133e22040bff7b0392153610117b0

Observation b06cedf5-b952-4952-9e47-b8bea3bee122 · outbound

This paper cites A fast iterative shrinkage-thresholding algo- rithm for linear inverse problems,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification A fast iterative shrinkage-thresholding algo- rithm for linear inverse problems,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-14T10:48:08.684307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:48:08.684307Z digest=sha256:6deae51da7a4e70fe71d6ccbe5997ce78b04d823c1f76eda2fb8b8e59988c82f

Observation ab7f4ff4-5206-4815-8b5a-28ebe1ea34dc · outbound

This paper cites Mars: A video benchmark for large-scale person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Mars: A video benchmark for large-scale person re-identification,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.052645Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.689995Z digest=sha256:89a9d6f0db452b8d0c70ef1c7e2e78bd79caee7d4612cd6992044d777ba37dd8

Observation c9c88c3a-3fb4-4e75-b686-25a449429cbc · outbound

This paper cites Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.033523Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.696013Z digest=sha256:10f402f8943a9c48edd608101f3e51505d521765a7e1a9006e9e4e5ad3f53419

Observation 4e7929d6-a6dd-43dc-b7f7-b7556a16ef99 · outbound

This paper cites Performance measures and a data set for multi-target, multi-camera tracking,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Performance measures and a data set for multi-target, multi-camera tracking,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:09.012169Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.700997Z digest=sha256:734a85df6f9c2c27c14974236c28e1dd9ddb84c6079b9af5eee6466c25530cdd

Observation bf987c57-49ab-4920-84a2-8f3af1a9b606 · outbound

This paper cites Person re-identification by local maximal occurrence representation and metric learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Person re-identification by local maximal occurrence representation and metric learning,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.994216Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.706282Z digest=sha256:a33dba40823299b0a2cab096b095c0ec13888d66a63f73f140d4eb1533a19da5

Observation b302c2d0-3df4-400c-aa0c-d8f70b18c60b · outbound

This paper cites Principal component analysis,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Principal component analysis,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.977692Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.711426Z digest=sha256:9b95088a17d0055ce6ea6cde175ddcaca41c24bccea229e7035f843166b70efd

Observation 941c780d-3af9-49de-bc0c-338e1160b43b · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification A density-based algorithm for discovering clusters in large spatial databases with noise

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.961208Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.716256Z digest=sha256:b6a1abf918ef878790e6821c8a1ef1c0cc24c247f963417c6a799f41f14cd2be

Observation 5de0c6ad-07a7-4a3a-a631-c553673d9bac · outbound

This paper cites Density-based clustering based on hierarchical density estimates,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Density-based clustering based on hierarchical density estimates,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.942880Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.721055Z digest=sha256:cce74c3d88718324f10811bb25f94968309ef13c5f135d9a4dbeb95e520df501

Observation 4cdfdf5d-17f7-4979-bfd7-54eb9d759161 · outbound

This paper cites Hierarchical density estimates for data clustering, visualization, and outlier detection,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Hierarchical density estimates for data clustering, visualization, and outlier detection,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.924633Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.726505Z digest=sha256:83fe7fcbf263e67d39e67847e76d41596a0f7f645de2fd1f2877623e306b483f

Observation 461aeb37-4007-4461-9d0a-baf3d6b518d5 · outbound

This paper cites Person re-identification by unsupervised 𝓁1 graph learning,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Person re-identification by unsupervised 𝓁1 graph learning,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.906008Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.731203Z digest=sha256:2d08a0dee51a9b860c356976008a45c7fea01281b6ee7827968fa86b2165a736

Observation cdbdff27-bfa9-43da-bdd1-80e812b46607 · outbound

This paper cites Unsupervised data association for met- ric learning in the context of multi-shot person re-identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised data association for met- ric learning in the context of multi-shot person re-identification,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.886737Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.736116Z digest=sha256:5f849d04a4487a98c83abe7c05a2753aab4c813e51f6a54ed8da47e25eadf6a5

Observation 454af7c2-6c4f-4a55-8b22-cc9a8ed607ff · outbound

This paper cites Unsupervised tracklet person re- identification,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Unsupervised tracklet person re- identification,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.869237Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.741027Z digest=sha256:b020ab5614c6f647c76de4d04d0c9c9be7b1b396a72ce35e7eec5de9222354a8

Observation 1cce4ad1-dbca-4f2a-9c36-aaf6fe2ac41c · outbound

This paper cites Progressive learning for person re-identification with one example,.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Progressive learning for person re-identification with one example,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:48:08.851752Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.745992Z digest=sha256:e7b8da455ff8cdb9383205da8c44cf7ddf832c92bc44c7021be9e7b98c1f4310

Observation b3784938-70a8-4ca6-8695-c688669c647e · outbound

This paper cites Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification.

Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:48:08.800996Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T10:48:08.751167Z digest=sha256:06dfaa173b982c8daa6c7ecd1243413ff4de34307e5a3630bbe84ce4d44dc5e2

Pith citing papers

No inbound Pith citation observations are available.