Paper Citation Record · LEDGER

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery

As of 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2606.05587.

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

pith.paper-citation-record.v1
2606.05587 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T02:48:27.383063Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

26 of 26 outbound references displayed

verified exact4
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c10ae4e0-5a46-4ed9-bfbe-e57830a4c9b7 · outbound

This paper cites VisDrone-MOT2019: The Vision Meets Drone Multiple Object Tracking Challenge Results.ICCV Workshops2019.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery VisDrone-MOT2019: The Vision Meets Drone Multiple Object Tracking Challenge Results.ICCV Workshops2019

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1c1d001-a00f-47ac-917d-2b85eaa7a359 · outbound

This paper cites VisDrone-DET2021: The Vision Meets Drone Object Detection Challenge Results.ICCV Workshops2021.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery VisDrone-DET2021: The Vision Meets Drone Object Detection Challenge Results.ICCV Workshops2021

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation add83984-f733-4e16-ade5-0818b913b89b · outbound

This paper cites Simple Online and Realtime Tracking.ICIP2016, 3464–3468.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Simple Online and Realtime Tracking.ICIP2016, 3464–3468

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04370b09-45da-44cd-b85e-6cbe44efdfdd · outbound

This paper cites Simple Online and Realtime Tracking with a Deep Association Metric.ICIP2017, 3645–3649.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Simple Online and Realtime Tracking with a Deep Association Metric.ICIP2017, 3645–3649

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7d18d1c-cdfd-41fa-9a5a-278c3f22276f · outbound

This paper cites ByteTrack: Multi-Object Tracking by Associating Every Detection Box.ECCV 2022, 1–21.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery ByteTrack: Multi-Object Tracking by Associating Every Detection Box.ECCV 2022, 1–21

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c02f349b-321c-4bae-881e-4302abeffdcc · outbound

This paper cites Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking.CVPR2023.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking.CVPR2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 112f69b4-fcc6-4db1-97c7-9b9331af2861 · outbound

This paper cites StrongSORT: Make DeepSORT Great Again.IEEE Trans.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery StrongSORT: Make DeepSORT Great Again.IEEE Trans

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd92f3a9-497a-4ff7-b012-d1def20a5dea · outbound

This paper cites Learning a Neural Solver for Multiple Object Tracking.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Learning a Neural Solver for Multiple Object Tracking

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d98f767b-7c7b-4885-8b18-3160387f4533 · outbound

This paper cites GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:56:55.179964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e08eac6c-51f0-4b2f-a5e7-4dc42e0ff2ff · outbound

This paper cites Towards Realtime Multi-Object Tracking.ECCV2020, 107–122.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Towards Realtime Multi-Object Tracking.ECCV2020, 107–122

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 565281fc-d99c-4113-a7ed-ed0a3bd6bffd · outbound

This paper cites TrackFormer: Multi- Object Tracking with Transformers.CVPR2022, 8844–8854.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery TrackFormer: Multi- Object Tracking with Transformers.CVPR2022, 8844–8854

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e245cb79-27bb-4d85-b1f9-e90648b76038 · outbound

This paper cites MOTR: End-to-End Multiple-Object Tracking with Transformer.ECCV2022, 145–161.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery MOTR: End-to-End Multiple-Object Tracking with Transformer.ECCV2022, 145–161

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5a398c6-d24b-480c-8743-4b137bf380fc · outbound

This paper cites Ultralytics YOLO (Version 8.0.0).GitHub2023.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Ultralytics YOLO (Version 8.0.0).GitHub2023

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d4e34da-f16b-44c7-90f2-86814405d46c · outbound

This paper cites Low-Altitude Multi-Object Tracking via Graph Neural Networks with Cross-Attention and Reliable Neighbor Guidance.Remote Sens.2025,17, 3502.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Low-Altitude Multi-Object Tracking via Graph Neural Networks with Cross-Attention and Reliable Neighbor Guidance.Remote Sens.2025,17, 3502

Reference 14

Resolution: verified exact; doi, observed 2026-06-28T02:51:30.361686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b257e388-fff0-4f47-a2f0-4345c7923363 · outbound

This paper cites SuperGlue: Learning Feature Matching with Graph Neural Networks.CVPR2020, 4938–4947.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery SuperGlue: Learning Feature Matching with Graph Neural Networks.CVPR2020, 4938–4947

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3564dae0-24de-4d06-b124-67d0d23d5fb0 · outbound

This paper cites In Defense of the Triplet Loss for Person Re-Identification.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery In Defense of the Triplet Loss for Person Re-Identification

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.171958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a0f12fdb-7afc-45a3-8dfe-5de78dc7aca8 · outbound

This paper cites Deep Residual Learning for Image Recognition.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Deep Residual Learning for Image Recognition

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a97cafa0-e687-4c42-bc23-051d35a61c2b · outbound

This paper cites Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking.ECCV Workshops2016, 17–35.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking.ECCV Workshops2016, 17–35

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2524f56-5943-498c-9821-9c958b892e22 · outbound

This paper cites HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking.IJCV2021, 129, 548–578.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking.IJCV2021, 129, 548–578

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e29c8e33-79c1-4ac7-aa31-5739289ddb6f · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.NeurIPS2015, 91–99.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.NeurIPS2015, 91–99

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b825338f-cfe6-49b9-99fc-dbfab4fac710 · outbound

This paper cites YOLOv3: An Incremental Improvement.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery YOLOv3: An Incremental Improvement

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.175602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3cce9f5e-b2e3-4745-befe-699a97ffcb5c · outbound

This paper cites Feature Pyramid Networks for Object Detection.CVPR2017, 2117–2125.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Feature Pyramid Networks for Object Detection.CVPR2017, 2117–2125

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6bd6762-6d07-40b7-8cd7-a5fdab64a1d6 · outbound

This paper cites Clustered Object Detection in Aerial Images.ICCV2019, 8311–8320.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Clustered Object Detection in Aerial Images.ICCV2019, 8311–8320

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4dca5e-eb10-436a-836c-5a364c3a8602 · outbound

This paper cites Finding Tiny Faces in the Wild with Generative Adversarial Network.CVPR2018, 21–30.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Finding Tiny Faces in the Wild with Generative Adversarial Network.CVPR2018, 21–30

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6d7bdb2-3c1c-4fa2-9d0c-51f1f4bd2069 · outbound

This paper cites The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking.ECCV 2018, 375–391.

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking.ECCV 2018, 375–391

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T02:48:27.383063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 126d11a5-da86-4700-bd90-5bb4589ee51f · outbound

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

HDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery Person Re-identification: Past, Present and Future

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:56:55.177104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.