Paper Citation Record · LEDGER

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos

As of 13 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2411.15895.

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

pith.paper-citation-record.v1
2411.15895 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:51:44.073542Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

36 of 36 outbound references displayed

verified exact0
verified fuzzy34
unresolved2
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff941324-4df8-45f4-a353-09b5faec495a · outbound

This paper cites Recent advances in intelligent processing of satellite video: Challenges, methods, and applications,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Recent advances in intelligent processing of satellite video: Challenges, methods, and applications,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.955039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e5745b9c-3135-430d-838c-3b53a142c26b · outbound

This paper cites Needles in a haystack: Tracking city- scale moving vehicles from continuously moving satellite,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Needles in a haystack: Tracking city- scale moving vehicles from continuously moving satellite,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.927692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cdc3e320-1455-40ac-a99e-0b9c35acdb57 · outbound

This paper cites Error bounded foreground and background modeling for moving object detection in satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Error bounded foreground and background modeling for moving object detection in satellite videos,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.903840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4a3cbed1-7747-4be3-b47b-6bc49ea3c5a1 · outbound

This paper cites Incorporating deep background prior into model-based method for unsupervised moving vehicle detection in satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Incorporating deep background prior into model-based method for unsupervised moving vehicle detection in satellite videos,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.883043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30f207ce-6afb-4b28-acaf-1a725cde4af0 · outbound

This paper cites Moving object detection by detecting contiguous outliers in the low-rank representation,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Moving object detection by detecting contiguous outliers in the low-rank representation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.858792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c6e60e2e-a626-4e7b-8d06-ebd4e83df284 · outbound

This paper cites Moving vehicle detection for remote sensing video surveillance with nonstationary satellite platform.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Moving vehicle detection for remote sensing video surveillance with nonstationary satellite platform

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.832926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fcef2389-708a-46f3-8c84-2d9ddca20a4d · outbound

This paper cites Moving object detection in satellite videos via spatial-temporal tensor model and weighted schatten p-norm minimization,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Moving object detection in satellite videos via spatial-temporal tensor model and weighted schatten p-norm minimization,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.809650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 51b64aae-533e-4cdd-8757-d6bf93c13136 · outbound

This paper cites Moving vehicle detection, tracking and traffic parameter estimation from a satellite video: A perspective on a smarter city,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Moving vehicle detection, tracking and traffic parameter estimation from a satellite video: A perspective on a smarter city,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.781528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9e78363b-8a82-4308-bbda-5a6e62c2e213 · outbound

This paper cites Detecting and tracking small and dense moving objects in satellite videos: A benchmark,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Detecting and tracking small and dense moving objects in satellite videos: A benchmark,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.759224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation af8bbc50-01c3-4617-9e40-d86b9334fccb · outbound

This paper cites Background subtraction based on low-rank and structured sparse decomposition,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Background subtraction based on low-rank and structured sparse decomposition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.734540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 74520992-1069-495a-98c3-20385ee277c6 · outbound

This paper cites Multi-channel fused lasso for motion detection in dynamic video scenarios,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Multi-channel fused lasso for motion detection in dynamic video scenarios,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.716778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88ef3005-1409-4369-b12f-0d7672ab04bf · outbound

This paper cites Background subtraction using spatio-temporal group sparsity recovery,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Background subtraction using spatio-temporal group sparsity recovery,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.698111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 69a89484-7865-4e55-b0ff-894ecb4425de · outbound

This paper cites Dsfnet: Dynamic and static fusion network for moving object detection in satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Dsfnet: Dynamic and static fusion network for moving object detection in satellite videos,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.673527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35c80502-2316-4702-a5b9-2eccad05338d · outbound

This paper cites Clusternet: Detecting small objects in large scenes by exploiting spatio-temporal information,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Clusternet: Detecting small objects in large scenes by exploiting spatio-temporal information,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.648616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dfdb5836-a606-45df-95ae-d65c72261e21 · outbound

This paper cites Very low- resolution moving vehicle detection in satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Very low- resolution moving vehicle detection in satellite videos,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.621095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a6878afa-6b20-456f-9458-bc9f1a8f0e12 · outbound

This paper cites Godec: Randomized low-rank & sparse matrix decomposition in noisy case,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Godec: Randomized low-rank & sparse matrix decomposition in noisy case,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.602627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bdf9e059-5ecb-4227-8e13-b62e8a418d47 · outbound

This paper cites Cross-frame foreground structural similarity modeling by convolutional sparse representation,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Cross-frame foreground structural similarity modeling by convolutional sparse representation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.578037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7ba26175-f46e-4f99-8568-3e91f02a496c · outbound

This paper cites Deep learning for generic object detection: A survey,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Deep learning for generic object detection: A survey,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.558250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4e0b8f40-5d79-4852-8255-96a012dfca59 · outbound

This paper cites A survey of the four pillars for small object detection: Multiscale representation, contextual information, super-resolution, and region proposal,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos A survey of the four pillars for small object detection: Multiscale representation, contextual information, super-resolution, and region proposal,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.534808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ebb6d75d-3150-4bb9-bd68-231a521d0ca1 · outbound

This paper cites Multiframe many–many point correspon- dence for vehicle tracking in high density wide area aerial videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Multiframe many–many point correspon- dence for vehicle tracking in high density wide area aerial videos,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.513603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dcdaf1ad-45d3-46da-a5be-311afdddd6fb · outbound

This paper cites Real-time tracking of low- resolution vehicles for wide-area persistent surveillance,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Real-time tracking of low- resolution vehicles for wide-area persistent surveillance,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.493719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f40eea1-ef1c-4dc1-a170-932103ff5449 · outbound

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

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos New generation deep learning for video object detection: A survey,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.471476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 389a8818-26e4-435d-b236-51473ad57118 · outbound

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

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Faster r-cnn: towards real-time object detection with region proposal networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.451067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e0560d38-cb93-4df0-9d75-851ed43297ce · outbound

This paper cites Objects as Points.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Objects as Points

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T13:51:43.993481Z

Source-reported events for the cited work

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Observation 29e526ab-c41b-4abd-996f-fb99235be01f · outbound

This paper cites Towards large-scale small object detection: Survey and benchmarks,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Towards large-scale small object detection: Survey and benchmarks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.427057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 215453ac-fbe1-4b3b-9900-52c8ae6b0054 · outbound

This paper cites Sdanet: Semantic- embedded density adaptive network for moving vehicle detection in satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Sdanet: Semantic- embedded density adaptive network for moving vehicle detection in satellite videos,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.402925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a9a0d3de-9a30-4dd6-ae22-7840d7725741 · outbound

This paper cites Graph moving object segmentation,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Graph moving object segmentation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.378218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 46d837f2-42be-4af8-ae54-cdce05ea158f · outbound

This paper cites Graph signal processing: History, development, impact, and outlook,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Graph signal processing: History, development, impact, and outlook,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.347174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 56532fdd-be21-4cab-8d73-676f482398c7 · outbound

This paper cites Discovering objects that can move,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Discovering objects that can move,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.324672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bda8959f-4b7c-4a08-a876-692093b3048e · outbound

This paper cites Large- scale unsupervised semantic segmentation,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Large- scale unsupervised semantic segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.303993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7a401b8b-b8cc-4b73-b292-9286ef6f94e9 · outbound

This paper cites Unsupervised online video object segmentation with motion property understanding,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Unsupervised online video object segmentation with motion property understanding,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.278422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8c20e9ce-696d-46e3-a0c4-d87f53919b01 · outbound

This paper cites Learning via watching: A weakly supervised moving object detector for satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Learning via watching: A weakly supervised moving object detector for satellite videos,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.254814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a62c635-7677-4308-bdcc-b067ad69a361 · outbound

This paper cites Simple online and realtime tracking,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Simple online and realtime tracking,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.228817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d26a7eab-dbfe-4f34-9687-e29b2d15fcb1 · outbound

This paper cites Online structured sparsity- based moving-object detection from satellite videos,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Online structured sparsity- based moving-object detection from satellite videos,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.199541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 99d3e612-5ecd-490b-849c-321033cd12ce · outbound

This paper cites From points to parts: 3d object detection from point cloud with part-aware and part- aggregation network,.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos From points to parts: 3d object detection from point cloud with part-aware and part- aggregation network,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:51:44.174818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3cc0cb32-0e12-4e70-bda3-11e5c6d4ac3f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos Adam: A Method for Stochastic Optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T13:51:44.073542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.