Paper Citation Record · LEDGER

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment

As of 24 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.24598.

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

pith.paper-citation-record.v1
2607.24598 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T10:58:35.439139Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

31 of 31 outbound references displayed

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Outbound references

Observation 9c6e4cba-285d-4aca-9f4f-69d2451f5679 · outbound

This paper cites End-to-end object detection with transformers,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment End-to-end object detection with transformers,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.307255Z

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Unavailable: canonical work link unavailable.

Observation 783767c4-e0a9-41eb-8d43-9dc6540b20bc · outbound

This paper cites Masked-attention mask transformer for universal image segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Masked-attention mask transformer for universal image segmentation,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.372720Z

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Observation c0dffed0-01e2-4cd8-991a-8f1d2156eda3 · outbound

This paper cites Seq- former: Sequential transformer for video instance seg- mentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Seq- former: Sequential transformer for video instance seg- mentation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.442996Z

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Observation edab6910-923a-4518-829d-456e7422eb8a · outbound

This paper cites In defense of online models for video instance segmen- tation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment In defense of online models for video instance segmen- tation,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.507883Z

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Observation f6140898-49e4-45a2-89e1-0776227811ac · outbound

This paper cites Visage: Video instance segmentation with appearance-guided enhancement,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Visage: Video instance segmentation with appearance-guided enhancement,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.563503Z

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Observation cad1075c-6918-4e50-b9af-4f7feefa43ae · outbound

This paper cites Minvis: A minimal video instance segmentation framework without video-based training,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Minvis: A minimal video instance segmentation framework without video-based training,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.635832Z

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Observation 0638f34a-3217-4976-9a95-1cf2a0de0319 · outbound

This paper cites A generalized framework for video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment A generalized framework for video instance segmentation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.705270Z

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Unavailable: canonical work link unavailable.

Observation 9954900b-112e-4a4f-9718-3aaf940cf07a · outbound

This paper cites Tcovis: Tempo- rally consistent online video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Tcovis: Tempo- rally consistent online video instance segmentation,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.789588Z

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Observation badad673-7af7-42ad-b5f5-5b0db16e7ccb · outbound

This paper cites Dvis: Decoupled video instance segmentation framework,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Dvis: Decoupled video instance segmentation framework,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.869090Z

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Observation c0cd4b19-15fb-4dc5-89f2-9b1ab9a4ef37 · outbound

This paper cites Cavis: Context-aware video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Cavis: Context-aware video instance segmentation,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:33.931745Z

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Observation c2a5ba52-1077-4d4e-a978-98dde57fd80a · outbound

This paper cites Lidar-camera fusion for video panoptic segmentation without video training,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Lidar-camera fusion for video panoptic segmentation without video training,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.010812Z

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Observation 9247b755-fd73-4a75-b7a3-067759679792 · outbound

This paper cites Mind the Gap: Disentangling Performance Bottlenecks in Video Instance Segmentation.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Mind the Gap: Disentangling Performance Bottlenecks in Video Instance Segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.054265Z

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Observation 100d4823-7740-47bb-b767-03d1f9bd81aa · outbound

This paper cites Per-pixel classification is not all you need for semantic segmen- tation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Per-pixel classification is not all you need for semantic segmen- tation,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.159602Z

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Observation 068634c6-7b7c-4737-8d88-a5f282de9e9b · outbound

This paper cites Video instance segmen- tation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Video instance segmen- tation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.218847Z

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Observation a9d0b735-d0e4-4712-ab2a-c591dbf00c07 · outbound

This paper cites Crossover learning for fast on- line video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Crossover learning for fast on- line video instance segmentation,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.280427Z

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Observation c17f4dd9-4c37-4692-87e0-ac930d6af10e · outbound

This paper cites VidEoMT: Your ViT is secretly also a video segmentation model,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment VidEoMT: Your ViT is secretly also a video segmentation model,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.363325Z

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Observation 22ed96f8-91dd-426a-8984-e0eb69d43288 · outbound

This paper cites NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.447852Z

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Observation 4e50b678-002c-4c99-a734-38665b8b0936 · outbound

This paper cites Efficient video instance segmentation via tracklet query and proposal,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Efficient video instance segmentation via tracklet query and proposal,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.511329Z

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Observation 376b6020-655d-4a71-a00a-60b124afbe09 · outbound

This paper cites Ctvis: Con- sistent training for online video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Ctvis: Con- sistent training for online video instance segmentation,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.582870Z

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Observation aec835aa-2eb4-48a1-b5c0-7bc7de1e8713 · outbound

This paper cites Visolo: Grid-based space-time aggregation for efficient online video instance segmen- tation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Visolo: Grid-based space-time aggregation for efficient online video instance segmen- tation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.642651Z

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Observation 155011e5-32a2-4ef7-99fc-81067040a24b · outbound

This paper cites Video instance segmentation using inter-frame communication transformers,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Video instance segmentation using inter-frame communication transformers,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.726895Z

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Observation d3b9db15-e4bd-4960-bba9-83afd1863d99 · outbound

This paper cites Vita: Video instance segmentation via object token as- sociation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Vita: Video instance segmentation via object token as- sociation,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.799758Z

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Observation 0354a5dc-b080-4a62-95e4-80c988c608f8 · outbound

This paper cites Mdqe: Mining discriminative query embeddings to segment occluded instances on challenging videos,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Mdqe: Mining discriminative query embeddings to segment occluded instances on challenging videos,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.891287Z

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Observation e5de03ed-1e0f-47e5-ae34-c6a97b1eb35d · outbound

This paper cites RefineVIS: Video Instance Segmentation with Temporal Attention Refinement.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment RefineVIS: Video Instance Segmentation with Temporal Attention Refinement

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:34.951024Z

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Observation 17a2e83c-953a-4dba-8d55-d63ea0e2a943 · outbound

This paper cites Sipmask: Spatial information preserva- tion for fast image and video instance segmentation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Sipmask: Spatial information preserva- tion for fast image and video instance segmentation,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.035346Z

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Observation f8e80bae-a73d-4ca3-95fa-7a52c568836e · outbound

This paper cites The 3rd large-scale video object segmentation challenge – video instance segmentation track,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment The 3rd large-scale video object segmentation challenge – video instance segmentation track,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.125591Z

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Observation 922e9a2f-485a-45ab-beaa-8a7c8b28af4b · outbound

This paper cites The 4th large-scale video object segmentation challenge – video instance segmen- tation track,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment The 4th large-scale video object segmentation challenge – video instance segmen- tation track,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.208422Z

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Observation 7ae57f54-e54a-4939-9c06-01c6aad4d1af · outbound

This paper cites Occluded video instance segmentation: A benchmark,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Occluded video instance segmentation: A benchmark,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.271268Z

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Observation 3728bd47-4a74-4f14-b168-7c54bacd48ab · outbound

This paper cites Deep residual learning for image recognition,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Deep residual learning for image recognition,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.332254Z

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Observation ae20e517-4a34-4748-93a3-674d923c2d0e · outbound

This paper cites Relational knowledge distillation,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Relational knowledge distillation,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.384836Z

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Observation 9232720a-19e8-49ae-ac86-dfb4d3afc8b9 · outbound

This paper cites Swin Transformer: Hierarchical vision transformer using shifted windows,.

QueenVIS: Rethinking Image-Only Training for Video Instance Segmentation via Query Enrichment Swin Transformer: Hierarchical vision transformer using shifted windows,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-31T10:58:35.439139Z

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Pith citing papers

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