Paper Citation Record · LEDGER

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles

As of 22 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.28483.

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

pith.paper-citation-record.v1
2607.28483 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T05:56:24.570940Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

20 of 20 outbound references displayed

verified exact0
verified fuzzy0
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 585b5bf8-1a17-4342-b6f2-d5a4bb6e6caa · outbound

This paper cites In: 2025 IEEE Real-Time Systems 12 L.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: 2025 IEEE Real-Time Systems 12 L

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:22.998095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d28e6c7b-4f55-4367-98dc-00a4117f2322 · outbound

This paper cites International Journal of Computer Vision129(11), 3119–3135 (2021).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles International Journal of Computer Vision129(11), 3119–3135 (2021)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.045668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ead26be6-e734-4ca9-9096-5e21f471182d · outbound

This paper cites In: IEEE/CVF CVPR.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF CVPR

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.154683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33fc0573-53b6-44cd-a2c8-f9a9d57d92a2 · outbound

This paper cites SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.337036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aec5e5c-007c-4988-95c8-18bfc1e2627c · outbound

This paper cites In: IEEE/CVF CVPR.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF CVPR

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.381486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e7b132d-5c55-4bc9-a3cb-7fecef0299f7 · outbound

This paper cites In: IEEE/CVF ICCV.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF ICCV

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.446303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a2028dc-1074-4c4a-bda1-fdea003cbe25 · outbound

This paper cites In: International Conference on Architectural Support for Programming Languages and Operating Systems.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: International Conference on Architectural Support for Programming Languages and Operating Systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.482707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed1d5d22-da68-44b4-bfb1-0ca7f629727b · outbound

This paper cites In: European Conference on Computer Vision (ECCV).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: European Conference on Computer Vision (ECCV)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.594749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 316445cf-b2f9-425e-95ed-b6cc6eb571fd · outbound

This paper cites In: IEEE/CVF ICCV.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF ICCV

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.736629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b8d6c52-c474-477e-a8d8-ca156723a57d · outbound

This paper cites Advances in Neural Information Processing Systems33, 21464–21475 (2020).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles Advances in Neural Information Processing Systems33, 21464–21475 (2020)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.806698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbce53d1-96b7-42f6-8e8c-38ecda8d4a59 · outbound

This paper cites In: IEEE/CVF ICCV.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF ICCV

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.862224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1462ed3-3f27-4438-9ec1-db3364358f29 · outbound

This paper cites arXiv:2602.22920 (2026).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles arXiv:2602.22920 (2026)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.921596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16e54c0d-8fde-445f-8e6f-aa165711d893 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles DINOv2: Learning Robust Visual Features without Supervision

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.977388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42e4b043-8179-43d9-9dd8-f7881bcfd389 · outbound

This paper cites In: IEEE/RSJ IROS.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/RSJ IROS

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.049143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b82ca34f-4e36-4ad3-b9e0-7abbba1e1bbb · outbound

This paper cites In: IEEE/CVF CVPR.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF CVPR

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.176920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79f1f2c8-f12c-40a9-bc5e-dd2c59a7be70 · outbound

This paper cites DINOv3.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles DINOv3

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.242719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f65eadb6-c80b-4234-be27-cfd622e40033 · outbound

This paper cites arXiv:2603.11441 (2026).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles arXiv:2603.11441 (2026)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.308793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5315943f-8b70-4a01-8a05-bfc94b508907 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2026).

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles IEEE Transactions on Pattern Analysis and Machine Intelligence (2026)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.374907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 271f4d67-86a1-4ab8-991a-a58f3c328ce2 · outbound

This paper cites In: IEEE/CVF CVPR Workshops.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF CVPR Workshops

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.454282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd7f85ad-00f1-40f5-a36e-054036f1da6d · outbound

This paper cites In: IEEE/CVF CVPR.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles In: IEEE/CVF CVPR

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:24.570940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.