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Paper Citation Record · LEDGER

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras

As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2506.06596.

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

pith.paper-citation-record.v1
2506.06596 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

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measured 43 of 43 standing notices

One-hop event checks from named stored sources.

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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

43 of 43 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9efdebc6-64fc-4bba-bd2b-12ed45cafd5a · outbound

This paper cites Neuromorphic vision-based motion segmentation with graph transformer neural network.Trans.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Neuromorphic vision-based motion segmentation with graph transformer neural network.Trans

Reference 1

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Observation a8055280-4c74-4516-8ca7-90e9f87365bf · outbound

This paper cites Motion segmentation for neu- romorphic aerial surveillance, 2024.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Motion segmentation for neu- romorphic aerial surveillance, 2024

Reference 2

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Observation b8c09385-66c7-4d55-8880-d3c1df2c9fdb · outbound

This paper cites Charbonnier, L.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Charbonnier, L

Reference 3

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Observation 66a3969f-5a92-4ed0-824b-ea132678db68 · outbound

This paper cites Focus is all you need: Loss functions for event-based vision.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Focus is all you need: Loss functions for event-based vision

Reference 4

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Observation 785c7309-18c0-40e4-96b2-7b9a906ec695 · outbound

This paper cites Davison, Jorg Conradt, Kostas Daniilidis, and Davide Scaramuzza.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Davison, Jorg Conradt, Kostas Daniilidis, and Davide Scaramuzza

Reference 5

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Observation aa15b4d9-96c2-4939-9485-3dce430e455b · outbound

This paper cites Opti- cal flow estimation from layered nearest neighbor flow fields.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Opti- cal flow estimation from layered nearest neighbor flow fields

Reference 6

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Observation 3cbe4a2e-16f8-4e54-b5fb-b82b93d58254 · outbound

This paper cites Dsec: A stereo event camera dataset for driv- ing scenarios.IEEE Robotics and Automation Letters, 6(3): 4947–4954, 2021.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Dsec: A stereo event camera dataset for driv- ing scenarios.IEEE Robotics and Automation Letters, 6(3): 4947–4954, 2021

Reference 7

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Observation 77d87c3e-f520-4a3a-9881-4a9ad03af61a · outbound

This paper cites Out of the Room: Generalizing Event-Based Dynamic Motion Seg- mentation for Complex Scenes.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Out of the Room: Generalizing Event-Based Dynamic Motion Seg- mentation for Complex Scenes

Reference 8

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Observation f4418a29-ea12-45fa-850d-28a3f229c387 · outbound

This paper cites Self-supervised learning of event-based optical flow with spiking neural networks.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Self-supervised learning of event-based optical flow with spiking neural networks

Reference 9

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Observation 099bb796-ea0b-4d6f-85a3-bc75b4cf5fdf · outbound

This paper cites Adam: A Method for Stochastic Optimization.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Adam: A Method for Stochastic Optimization

Reference 10

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Observation 38bc0062-381b-40d6-a6b4-e028b358df5c · outbound

This paper cites Kumar, Philip Torr, and A.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Kumar, Philip Torr, and A

Reference 11

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Observation f9738fa0-419f-42d3-bd1f-4672c7fc77d7 · outbound

This paper cites Spike-flownet: Event-based optical flow estimation with energy-efficient hy- brid neural networks.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Spike-flownet: Event-based optical flow estimation with energy-efficient hy- brid neural networks

Reference 12

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Observation 0b60e133-28f4-4bca-8f71-d4b16947ecf8 · outbound

This paper cites Fusion-flownet: Energy-efficient optical flow estimation us- ing sensor fusion and deep fused spiking-analog network ar- chitectures.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Fusion-flownet: Energy-efficient optical flow estimation us- ing sensor fusion and deep fused spiking-analog network ar- chitectures

Reference 13

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Observation 3dad2ec3-8214-4ad7-8617-f928b2033c3f · outbound

This paper cites an unresolved cited work.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Unresolved cited work

Reference 14

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Observation 77c041bf-e751-47a4-bad0-8a949ebcc9be · outbound

This paper cites A lightweight net- work to learn optical flow from event data.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras A lightweight net- work to learn optical flow from event data

Reference 15

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Observation 8bb3d471-4aa8-4784-85f0-31e9f179639e · outbound

This paper cites Microsoft COCO: Common Objects in Context.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Microsoft COCO: Common Objects in Context

Reference 16

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Observation 791a390e-56e4-4c80-afc1-99aa268f12cf · outbound

This paper cites See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks

Reference 17

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Observation 2731b29c-ed82-4a51-ab3a-cedab285a0fa · outbound

This paper cites Event-based moving object detection and tracking.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Event-based moving object detection and tracking

Reference 18

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Observation 419e71c5-28d9-4b33-9d0b-c68408dce5cd · outbound

This paper cites Learning visual motion segmentation using event surfaces.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Learning visual motion segmentation using event surfaces

Reference 19

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Observation 2a3985cd-83c6-4048-8b58-97f4ab6bf55a · outbound

This paper cites Parameshwara, Simin Li, Cornelia Ferm ¨uller, Nitin J.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Parameshwara, Simin Li, Cornelia Ferm ¨uller, Nitin J

Reference 20

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Observation a630d4ad-75ad-4a16-92fa-2ffd7aeeb2b4 · outbound

This paper cites Parameshwara, Nitin J.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Parameshwara, Nitin J

Reference 21

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Observation d72fefc7-7fd8-4a4c-8b3f-55aa8aa2cdab · outbound

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EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Unresolved cited work

Reference 22

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Observation b935de38-f10b-4f81-a4ee-17966e3f5f4e · outbound

This paper cites Learning features by watching ob- jects move.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Learning features by watching ob- jects move

Reference 23

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Observation e4771ba0-5496-422d-8dbd-195f5d2b13b4 · outbound

This paper cites ESIM: an open event camera simulator.Conf.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras ESIM: an open event camera simulator.Conf

Reference 24

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Observation c2b12d88-13a2-4c9a-bb51-f59374894961 · outbound

This paper cites Sanket, Chethan M.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Sanket, Chethan M

Reference 25

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Observation 310c3eef-ff22-4901-9e10-9e9631336303 · outbound

This paper cites Learning to segment dominant object motion from watching videos.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Learning to segment dominant object motion from watching videos

Reference 26

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Observation 22a87e09-ad31-4013-94ff-33e8e2db8b9a · outbound

This paper cites Event-based motion segmentation by motion compensation.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Event-based motion segmentation by motion compensation

Reference 27

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Observation bf098d01-d7b6-4625-b2f2-9ffa0654fad0 · outbound

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EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Unresolved cited work

Reference 28

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Observation ace91c72-dbd5-4c72-8053-1f8bc54e62c3 · outbound

This paper cites Wang and E.H.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Wang and E.H

Reference 29

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Observation a1d7fabf-9366-49d1-86d1-cd18da0c9fe7 · outbound

This paper cites Un- evmoseg: Unsupervised event-based independent motion segmentation, 2023.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Un- evmoseg: Unsupervised event-based independent motion segmentation, 2023

Reference 30

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Source-reported events for the cited work

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Observation 02aa41bb-e28c-436c-8bb3-619eded0574a · outbound

This paper cites Self-supervised video object segmentation by motion grouping.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Self-supervised video object segmentation by motion grouping

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 92cc8d14-51a5-4ac0-afd7-61cdfa823423 · outbound

This paper cites Multi-motion and ap- pearance self-supervised moving object detection.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Multi-motion and ap- pearance self-supervised moving object detection

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 32e30a19-1330-43a8-970d-b3fc36ddf26f · outbound

This paper cites Unsupervised moving object detection via contextual information separation.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Unsupervised moving object detection via contextual information separation

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 32bb9a2c-f708-40e2-bced-d5b5717274e6 · outbound

This paper cites Yorke, and Yiannis Aloimonos.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Yorke, and Yiannis Aloimonos

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9988a484-9ea6-4d88-9b21-3dad332c4f09 · outbound

This paper cites Deformable sprites for unsupervised video decomposition.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Deformable sprites for unsupervised video decomposition

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.858189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.617742Z digest=sha256:63347807a244f66f47e42924ff14ac15652ff6c9a9c80495c8fe49a5e5dcc866

Observation 9fc9b63f-a59f-4304-b29a-38d774f00f9c · outbound

This paper cites BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T05:57:25.622787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:57:25.622787Z digest=sha256:cb9de4f342382631b950ce47447945881956e5bc14f4f74b0e360f1c7be9832e

Observation 30b603b0-c355-471e-ab6f-15fa02f26c58 · outbound

This paper cites Enhanced local subspace affinity for feature- based motion segmentation.Pattern Recognition, 44:454– 470, 2011.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Enhanced local subspace affinity for feature- based motion segmentation.Pattern Recognition, 44:454– 470, 2011

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.842062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.627799Z digest=sha256:88ba473d6e95e213d5b571aaf8fc4a13f5392d614dedb9edc6e2304a6f1cc443

Observation 4d52166d-fc35-48b1-a194-6930dfdf4d60 · outbound

This paper cites Event-enhanced snapshot compressive videography at 10k fps.IEEE Trans.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Event-enhanced snapshot compressive videography at 10k fps.IEEE Trans

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.825101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.632362Z digest=sha256:26c3d1c8ea7033316b05eaf61c46f2da8fedafe537b46f993d3af205a3fc661a

Observation a2828d97-67e2-429f-9a0e-634c72e362d8 · outbound

This paper cites Permutation pref- erence based alternate sampling and clustering for motion segmentation.IEEE Signal Processing Letters, 25(3):432– 436, 2018.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Permutation pref- erence based alternate sampling and clustering for motion segmentation.IEEE Signal Processing Letters, 25(3):432– 436, 2018

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.808885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.637577Z digest=sha256:18a37addb8737cf9afa77cdbfbde759edb4f404aa6c3d498dac07381f1d9fbef

Observation 8c251780-3c50-4923-9044-b0bd04271beb · outbound

This paper cites Event-based motion segmentation with spatio- temporal graph cuts.IEEE Transactions on Neural Networks and Learning Systems, pages 1–13, 2021.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Event-based motion segmentation with spatio- temporal graph cuts.IEEE Transactions on Neural Networks and Learning Systems, pages 1–13, 2021

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.792732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.642519Z digest=sha256:a6cc849150e36a6632edc5d94e211c4ebd8e036124185d2ef76b043633ae9eed

Observation 5c70b7df-1791-45b4-b916-3b2211ae44dd · outbound

This paper cites The multi- vehicle stereo event camera dataset: An event camera dataset for 3d perception.IEEE Robotics and Automation Letters, 3 (3):2032–2039, 2018.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras The multi- vehicle stereo event camera dataset: An event camera dataset for 3d perception.IEEE Robotics and Automation Letters, 3 (3):2032–2039, 2018

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.775073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.647171Z digest=sha256:7e397ec3707a4d8b36c008459d1c838287445d902be92a6ef87ce2b554689a98

Observation 4a04de31-b09a-4649-90c8-c94307c52395 · outbound

This paper cites EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T05:57:25.651673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:57:25.651673Z digest=sha256:72d9dd253a1068f1ed978ba4018701e3c708712815e055c342f941c80adf12b3

Observation 30f47ba4-c8b7-42d9-88ae-e3742a6205f9 · outbound

This paper cites Unsupervised event-based learning of op- tical flow, depth, and egomotion.

EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras Unsupervised event-based learning of op- tical flow, depth, and egomotion

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:57:25.757926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T05:57:25.657627Z digest=sha256:260dcdee48ce54b4ffa4bc5f069b72e7d362bf9706e5b012fbea2b70cde42699

Pith citing papers

No inbound Pith citation observations are available.