Paper Citation Record · LEDGER

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.20550.

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

pith.paper-citation-record.v1
2506.20550 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:50:43.557595Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact1
verified fuzzy15
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 819cf284-94c8-4197-9474-47130028480b · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:40.128704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d675ffdc-ce47-4dc7-94cf-d828bbde0c24 · outbound

This paper cites Recurrent neural networks for video object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Recurrent neural networks for video object detection,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.977906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7a2d0391-6822-4c50-ac39-10360c64c210 · outbound

This paper cites Flow-guided feature aggregation for video object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Flow-guided feature aggregation for video object detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.963750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5f51163e-2f4e-49bb-a51c-149cb56211ce · outbound

This paper cites Sequence level seman- tics aggregation for video object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Sequence level seman- tics aggregation for video object detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.949297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aae06bcf-f8d0-49da-a300-b78902796f9c · outbound

This paper cites Slowfast networks for video recognition,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Slowfast networks for video recognition,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:40.676193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e603338-f870-43fd-b7cc-3e32a8c12652 · outbound

This paper cites A brief introduction to weakly supervised learning,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos A brief introduction to weakly supervised learning,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:40.812950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f543736c-604c-4501-845b-1d477d804e65 · outbound

This paper cites MOT20: A benchmark for multi object tracking in crowded scenes.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos MOT20: A benchmark for multi object tracking in crowded scenes

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:41.211905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3cd499d-a79e-4c78-86a9-3f3421c1317e · outbound

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

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Faster r-cnn: Towards real- time object detection with region proposal networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.881151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8bcca8c7-d2a2-4ae9-8915-d5c1d56c94af · outbound

This paper cites You only look once: Unified, real-time object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos You only look once: Unified, real-time object detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.577983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aac0882c-a9c4-436a-81a8-b3f5b714930f · outbound

This paper cites Focal loss for dense object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Focal loss for dense object detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.266270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e3995a0-7f80-4580-926d-c92be1bb7f55 · outbound

This paper cites A detailed study of the association task in tracking-by- detection-based multi-person tracking,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos A detailed study of the association task in tracking-by- detection-based multi-person tracking,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:45.091877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c8bde5fb-6667-432d-84d3-43eb09eb114f · outbound

This paper cites Video object detection with an aligned spatial-temporal memory,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Video object detection with an aligned spatial-temporal memory,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.961372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a184505b-27c6-4736-8ccb-45cd45e4f3b8 · outbound

This paper cites Learning recurrent memory activation networks for visual tracking,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Learning recurrent memory activation networks for visual tracking,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.800024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 92a80f96-5f9d-4ec5-a1c4-0e24d7b3bb36 · outbound

This paper cites Video visual relation detection via 3d convolutional neural network,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Video visual relation detection via 3d convolutional neural network,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.670775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 95f5e276-5813-43e9-815a-5a3f918887ad · outbound

This paper cites An Efficient 3D CNN for Action/Object Segmentation in Video.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos An Efficient 3D CNN for Action/Object Segmentation in Video

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:50:43.708852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 78cf56d1-e896-4a85-8bfb-0d187447940d · outbound

This paper cites New generation deep learning for video object detection: A survey,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos New generation deep learning for video object detection: A survey,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.525546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b89d4ad5-65cc-4e4c-a04f-d3ad2dfaf949 · outbound

This paper cites Label- efficient online continual object detection in streaming video,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Label- efficient online continual object detection in streaming video,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.368875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e834f025-55b6-486d-a7c4-ceeda7efb76a · outbound

This paper cites A review of video object detection: Datasets, metrics and methods,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos A review of video object detection: Datasets, metrics and methods,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.195751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f2c17c79-b7af-4a9c-9df3-2dc4c0f6a602 · outbound

This paper cites Yolov: Making still image object detectors great at video object detection,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Yolov: Making still image object detectors great at video object detection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:44.098627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8c45a11b-ce2c-4d9d-b860-161963fdda8c · outbound

This paper cites Seadronessee: A maritime benchmark for detecting humans in open water,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Seadronessee: A maritime benchmark for detecting humans in open water,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:50:43.926569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e55fc948-bcba-4147-aaee-ec7062ebcbee · outbound

This paper cites The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.153310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aeb32941-9aeb-4d57-9a83-44795dc8bf24 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.245635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 299c51e6-379c-4aff-acb1-8f1316e73b23 · outbound

This paper cites Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.305234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5263cb3c-6fb4-4250-80cf-b4fd45eaecf9 · outbound

This paper cites Eigen-cam: Class activation map using principal components,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Eigen-cam: Class activation map using principal components,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.369754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef6b1acd-d479-47ce-bead-59397ff12127 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Imagenet classification with deep convolutional neural networks,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.468469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76791451-a0dc-42d6-a6cd-5ca0fc1fd5b0 · outbound

This paper cites Microsoft coco: Common objects in context,.

Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos Microsoft coco: Common objects in context,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:43.557595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.