Paper Citation Record · LEDGER

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.05229.

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

pith.paper-citation-record.v1
2507.05229 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:34:06.828246Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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 exact0
verified fuzzy30
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8fc06bc7-d7e4-4bd9-982d-e49cf69fee8c · outbound

This paper cites Simple online and realtime tracking.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Simple online and realtime tracking

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:12.925966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bcf21fff-9cd3-4bf5-8b82-5061b205c664 · outbound

This paper cites End-to-end object detec- tion with transformers.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage End-to-end object detec- tion with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:12.398312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bc7c9d37-bd51-4d4c-ac50-87ac57496649 · outbound

This paper cites 1 C filter: a simple speed-based low-pass filter for noisy input in interactive systems.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage 1 C filter: a simple speed-based low-pass filter for noisy input in interactive systems

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:12.194573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2644a090-1486-436d-9cce-060c0a34a911 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage A simple framework for contrastive learning of visual representations

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:11.973473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c1920ac3-a5f7-4004-acb7-2b83faa676c2 · outbound

This paper cites A simple framework for contrastive learning of visual representations, 2020.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage A simple framework for contrastive learning of visual representations, 2020

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:04.547149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36da2a21-c158-48e4-ae33-c64660c00631 · outbound

This paper cites An assessment of multi-object tracking under low framerate conditions.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage An assessment of multi-object tracking under low framerate conditions

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:11.766362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1943c440-4c15-40f0-8664-ae7c88bc48e6 · outbound

This paper cites Mask r-cnn, 2018.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Mask r-cnn, 2018

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:11.561438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fc61b68c-92f1-4e6d-a073-568c9ee3f8a4 · outbound

This paper cites Deep residual learning for image recognition, 2015.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Deep residual learning for image recognition, 2015

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:04.751298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6140980f-a8c3-4e57-a267-c598a26c9364 · outbound

This paper cites Occlusion and motion reasoning for long-term tracking.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Occlusion and motion reasoning for long-term tracking

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:11.355879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f41ff4c5-5828-4204-8963-31162a628a00 · outbound

This paper cites segment anything.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage segment anything

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:11.184415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 80d83f3c-1b32-45fd-84df-ce12c6b4ac2e · outbound

This paper cites an unresolved cited work.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:34:10.931314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2928c7bf-68b3-4fd1-8829-0e1d213f23ac · outbound

This paper cites Oc-sort: Observation- centric sort for robust multi-object tracking, 2022.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Oc-sort: Observation- centric sort for robust multi-object tracking, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:10.755252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 57e62418-e024-4239-809c-78e5869578d2 · outbound

This paper cites Supervised contrastive learning, 2021.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Supervised contrastive learning, 2021

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:10.541470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9fac427a-33d1-4c5f-8565-7cf678995201 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:05.223112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c04b518-0aab-4f26-8f23-9dfada299ac7 · outbound

This paper cites APPTracker: Appearance and prediction probability tracker for low-fps scenarios.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage APPTracker: Appearance and prediction probability tracker for low-fps scenarios

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:10.334197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 76e49aaa-98b7-4050-89a2-80c826f67810 · outbound

This paper cites Collaborative tracking learning for frame-rate-insensitive multi-object tracking, 2023.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Collaborative tracking learning for frame-rate-insensitive multi-object tracking, 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:10.136253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f914f337-8f81-422a-bdd8-8c6d08d66721 · outbound

This paper cites Huang, and Fisher Yu.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Huang, and Fisher Yu

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.950315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c439083a-f282-411d-b10a-11ad26404a4c · outbound

This paper cites Matching anything by segmenting anything, 2024.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Matching anything by segmenting anything, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.748665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b28ca4a-1511-43ea-90f4-67dced898ba2 · outbound

This paper cites Multi-object tracking meets moving uav.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Multi-object tracking meets moving uav

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.571902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 763bfc56-8065-4828-8387-44a0601156aa · outbound

This paper cites MeMOTR: Memory-enhanced multiple object tracking with transformers.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage MeMOTR: Memory-enhanced multiple object tracking with transformers

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.409008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 39d90a67-b2fd-4ad9-9585-94b84878e14a · outbound

This paper cites Trackformer: Multi-object tracking with transformers, 2022.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Trackformer: Multi-object tracking with transformers, 2022

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.242938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f98d7f94-6e72-4e2f-aeca-8792d566127f · outbound

This paper cites Quasi-Dense Similarity Learning for Multiple Object Tracking, 2024.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Quasi-Dense Similarity Learning for Multiple Object Tracking, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:09.070229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 29a29743-384b-413c-bece-9651abae72ff · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks, 2016.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Faster r-cnn: Towards real-time object detection with region proposal networks, 2016

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:05.901632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 567a711b-469c-4d53-96fb-06663282f818 · outbound

This paper cites Adapt- ing the segment anything model during usage in novel situations, 2024.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Adapt- ing the segment anything model during usage in novel situations, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:08.862557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1cf4947f-327b-4121-9aa8-9286ece9bd71 · outbound

This paper cites Boosttrack: boosting the similarity measure and detection confidence for improved multiple object tracking.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Boosttrack: boosting the similarity measure and detection confidence for improved multiple object tracking

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:08.669946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 56916b85-b1ca-4f81-a298-541532b800fb · outbound

This paper cites FraMOT: Frame- adaptive multi-object tracking in low framerate conditions, 2022.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage FraMOT: Frame- adaptive multi-object tracking in low framerate conditions, 2022

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:08.521397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f34821f4-6665-407c-847d-cdbc46dea414 · outbound

This paper cites Can sam segment anything? when sam meets camouflaged object detection, 2023.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Can sam segment anything? when sam meets camouflaged object detection, 2023

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:08.329087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9470e702-6963-46a8-8dd0-6c9f4216b6dc · outbound

This paper cites Simple online and realtime tracking with a deep association metric, 2017.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Simple online and realtime tracking with a deep association metric, 2017

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:08.104958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5aa34946-b857-4d5b-a245-636fcf4e6bff · outbound

This paper cites Segment-anything models achieve zero-shot robustness in autonomous driving, 2024.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Segment-anything models achieve zero-shot robustness in autonomous driving, 2024

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.944970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8db0c863-695d-49ef-9ad9-0dcb16031523 · outbound

This paper cites Self-supervised multi-object tracking with path consistency, 2023.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Self-supervised multi-object tracking with path consistency, 2023

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.773642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bab11357-fbe5-4266-adf0-5dbfd4afc433 · outbound

This paper cites MOTR: End-to-end multiple-object tracking with trans- former.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage MOTR: End-to-end multiple-object tracking with trans- former

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.642884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fbb5e737-b58b-478f-929b-b8210f4b4592 · outbound

This paper cites MOTRv3: Refined multiple object tracking with transformers.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage MOTRv3: Refined multiple object tracking with transformers

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.486160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 661135a8-a8b2-4e9f-82b0-6f8e01869c7e · outbound

This paper cites Bytetrack: Multi- object tracking by associating every detection box, 2022.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Bytetrack: Multi- object tracking by associating every detection box, 2022

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.332663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b611d4f2-e06c-44eb-a769-0729a8fd89c6 · outbound

This paper cites Fairmot: On the fairness of detection and re-identification in multiple object tracking, 2020.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage Fairmot: On the fairness of detection and re-identification in multiple object tracking, 2020

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.156766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 00522694-031b-47cf-b1b3-6935d136f7f3 · outbound

This paper cites CenterTrack: Tracking objects as points.

Self-Supervised Real-Time Tracking of Military Vehicles in Low-FPS UAV Footage CenterTrack: Tracking objects as points

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:34:07.014103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.