Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos | Paper Citation Record

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This paper cites N2f2: Hierarchical scene under- standing with nested neural feature fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos N2f2: Hierarchical scene under- standing with nested neural feature fields

Reference 1

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Observation 0a90dc78-1007-4218-b00e-502c3f5c52ff · outbound

This paper cites Hen- riques, Andrea Vedaldi, and Andrew Zisserman.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Hen- riques, Andrea Vedaldi, and Andrew Zisserman

Reference 2

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This paper cites Henriques, Andrea Vedaldi, and Andrew Zisserman.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Henriques, Andrea Vedaldi, and Andrew Zisserman

Reference 3

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This paper cites It’s moving! a prob- abilistic model for causal motion segmentation in moving camera videos.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos It’s moving! a prob- abilistic model for causal motion segmentation in moving camera videos

Reference 4

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This paper cites Traditional and recent approaches in background modeling for foreground detection: An overview.Computer science review, 11:31–66, 2014.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Traditional and recent approaches in background modeling for foreground detection: An overview.Computer science review, 11:31–66, 2014

Reference 5

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Observation 6daa1299-ed81-48c6-b65b-f4ff29df3e10 · outbound

This paper cites Object segmentation by long term analysis of point trajectories.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Object segmentation by long term analysis of point trajectories

Reference 6

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This paper cites Hexplane: A fast representa- tion for dynamic scenes.Proceedings of the IEEE Confer- ence on Computer Vision and Pattern Recognition (CVPR),.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Hexplane: A fast representa- tion for dynamic scenes.Proceedings of the IEEE Confer- ence on Computer Vision and Pattern Recognition (CVPR),

Reference 7

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Observation 6a33cb8f-f936-4f3d-86e4-15d331f3cb26 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Emerging properties in self-supervised vision transformers

Reference 8

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Observation f6e04f13-fb3e-4592-a267-1be79fc25b21 · outbound

This paper cites Self-supervised learning with geometric constraints in monocular video: Connecting flow, depth, and camera.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Self-supervised learning with geometric constraints in monocular video: Connecting flow, depth, and camera

Reference 9

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Observation 14642468-d6c8-4795-89d7-0d57b5ef41f8 · outbound

This paper cites Guess What Moves: Unsupervised Video and Image Segmentation by Anticipat- ing Motion.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Guess What Moves: Unsupervised Video and Image Segmentation by Anticipat- ing Motion

Reference 10

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Observation 153316d2-0951-445d-bb8d-24780667a628 · outbound

This paper cites Csurka, C.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Csurka, C

Reference 11

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Observation fdae47fa-7b0d-4c55-90a5-0de3a9fe4498 · outbound

This paper cites Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100.Interna- tional Journal of Computer Vision (IJCV), 2022.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100.Interna- tional Journal of Computer Vision (IJCV), 2022

Reference 12

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This paper cites An im- age is worth 16×16 words: Transformers for image recog- nition at scale.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos An im- age is worth 16×16 words: Transformers for image recog- nition at scale

Reference 13

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Observation e807beb9-69c4-4cd6-9d70-b7afec58f917 · outbound

This paper cites Tenen- baum, and Jiajun Wu.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Tenen- baum, and Jiajun Wu

Reference 14

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This paper cites NeRF-SOS: Any-view self- supervised object segmentation on complex scenes.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos NeRF-SOS: Any-view self- supervised object segmentation on complex scenes

Reference 15

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This paper cites Fast dynamic radiance fields with time-aware neural voxels.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fast dynamic radiance fields with time-aware neural voxels

Reference 16

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This paper cites K- planes: Explicit radiance fields in space, time, and appear- ance.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos K- planes: Explicit radiance fields in space, time, and appear- ance

Reference 17

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Observation c7aa225a-b31e-4220-9de1-097808c9ed3d · outbound

This paper cites Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation

Reference 18

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This paper cites Dynamic View Synthesis from Dynamic Monocular Video.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Dynamic View Synthesis from Dynamic Monocular Video

Reference 19

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Observation 4448c332-d160-460b-b607-b7635b35adc4 · outbound

This paper cites Monocular dynamic view synthe- sis: A reality check.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Monocular dynamic view synthe- sis: A reality check

Reference 20

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This paper cites Monocular Dynamic View Synthesis: A Reality Check.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Monocular Dynamic View Synthesis: A Reality Check

Reference 21

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This paper cites Girshick.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Girshick

Reference 22

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This paper cites Neural deformable voxel grid for fast optimization of dynamic view synthe- sis.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Neural deformable voxel grid for fast optimization of dynamic view synthe- sis

Reference 23

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Observation bf0c3170-91d6-4e0f-a69c-67bd2511e917 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Deep Residual Learning for Image Recognition

Reference 24

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Observation 3a8fd15e-f251-4fd2-b2fe-0a56a044f275 · outbound

This paper cites Dense 3d semantic mapping of indoor scenes from rgb- d images.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Dense 3d semantic mapping of indoor scenes from rgb- d images

Reference 25

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This paper cites Sfm-ttr: Using struc- ture from motion for test-time refinement of single-view depth networks.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Sfm-ttr: Using struc- ture from motion for test-time refinement of single-view depth networks

Reference 26

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This paper cites Fusion- seg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fusion- seg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos

Reference 27

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This paper cites What uncertainties do we need in Bayesian deep learning for computer vision?Proceed- ings of Advances in Neural Information Processing Systems (NeurIPS), 2017.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos What uncertainties do we need in Bayesian deep learning for computer vision?Proceed- ings of Advances in Neural Information Processing Systems (NeurIPS), 2017

Reference 28

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Observation cde6e65d-06e1-4665-a7a0-b47ad0e86a12 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42(4), 2023.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos 3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics, 42(4), 2023

Reference 29

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This paper cites Lerf: Language embed- ded radiance fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Lerf: Language embed- ded radiance fields

Reference 30

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This paper cites GARField: Group Anything with Radiance Fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos GARField: Group Anything with Radiance Fields

Reference 31

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This paper cites Decomposing neRF for editing via feature field dis- tillation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Decomposing neRF for editing via feature field dis- tillation

Reference 32

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Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 33

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This paper cites Joint semantic segmentation and 3d re- construction from monocular video.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Joint semantic segmentation and 3d re- construction from monocular video

Reference 34

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This paper cites Panoptic neural fields: A semantic object-aware neural scene rep- resentation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Panoptic neural fields: A semantic object-aware neural scene rep- resentation

Reference 35

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This paper cites Divided attention: Unsuper- vised multiple-object discovery and segmentation with in- terpretable contextually separated slots, 2024.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Divided attention: Unsuper- vised multiple-object discovery and segmentation with in- terpretable contextually separated slots, 2024

Reference 36

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This paper cites Language-driven semantic seg- mentation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Language-driven semantic seg- mentation

Reference 37

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This paper cites New- combe, and Zhaoyang Lv.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos New- combe, and Zhaoyang Lv

Reference 38

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This paper cites Neural scene flow fields for space-time view synthe- sis of dynamic scenes.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Neural scene flow fields for space-time view synthe- sis of dynamic scenes

Reference 39

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This paper cites Dynibar: Neural dynamic image-based rendering.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Dynibar: Neural dynamic image-based rendering

Reference 40

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Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 41

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This paper cites A comprehensive sur- vey on test-time adaptation under distribution shifts, 2023.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos A comprehensive sur- vey on test-time adaptation under distribution shifts, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.958171Z

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This paper cites Semantic attention flow fields for monocular dynamic scene decomposition.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Semantic attention flow fields for monocular dynamic scene decomposition

Reference 43

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This paper cites Devrf: Fast deformable voxel radi- ance fields for dynamic scenes.Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 35: 36762–36775, 2022.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Devrf: Fast deformable voxel radi- ance fields for dynamic scenes.Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 35: 36762–36775, 2022

Reference 44

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Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 45

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This paper cites Multi-view deep learning for consistent semantic mapping with RGB-D cameras.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Multi-view deep learning for consistent semantic mapping with RGB-D cameras

Reference 46

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This paper cites Marr.Vision: A computational investigation into the human representation and processing of visual information.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Marr.Vision: A computational investigation into the human representation and processing of visual information

Reference 47

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Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 48

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Observation bcf56a33-3ca2-48f5-8f8e-3747b97e2b76 · outbound

This paper cites Dif- fuser: Multi-view 2D-to-3D label diffusion for semantic scene segmentation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Dif- fuser: Multi-view 2D-to-3D label diffusion for semantic scene segmentation

Reference 49

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This paper cites A review of motion segmentation: Approaches and ma- jor challenges.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos A review of motion segmentation: Approaches and ma- jor challenges

Reference 50

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This paper cites Scene chronology.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Scene chronology

Reference 51

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Observation 0f04b6e8-8138-4ee0-837f-11ac0205f62d · outbound

This paper cites Semanticfusion: Dense 3d seman- tic mapping with convolutional neural networks.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Semanticfusion: Dense 3d seman- tic mapping with convolutional neural networks

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Observation 31463bce-387f-4d79-8a27-9b3e41419593 · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Srinivasan, Matthew Tancik, Jonathan T

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.845733Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d9514a63-1e18-4e45-91f1-0676a3001fa3 · outbound

This paper cites Laterf: Label and text driven object radi- ance fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Laterf: Label and text driven object radi- ance fields

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.835168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c81af0e3-d36b-415b-b02b-fee43f4174e5 · outbound

This paper cites Learning visual motion segmentation using event surfaces.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Learning visual motion segmentation using event surfaces

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.823565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 70d0a7df-8484-4e14-856a-fa64b37ae48b · outbound

This paper cites Panopticfusion: Online volumetric semantic map- ping at the level of stuff and things.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Panopticfusion: Online volumetric semantic map- ping at the level of stuff and things

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.813422Z

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Observation c8d7570e-dca3-426a-a43f-7621e8f3dfe9 · outbound

This paper cites Captur- ing the geometry of object categories from video supervi- sion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Captur- ing the geometry of object categories from video supervi- sion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.802329Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 62e155e2-ab1a-4376-a207-3c71a5f42846 · outbound

This paper cites an unresolved cited work.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:24:25.791449Z

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Observation 6609327f-88b7-4c85-82ee-d3b0828454c6 · outbound

This paper cites Neural scene graphs for dynamic scenes.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Neural scene graphs for dynamic scenes

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.781354Z

Source-reported events for the cited work

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Observation 817752e0-7648-42d6-a415-3cb1b28d4a47 · outbound

This paper cites Fast object seg- mentation in unconstrained video.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fast object seg- mentation in unconstrained video

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.771993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3a380a6d-7eeb-4642-8e34-5f3053a2c7fe · outbound

This paper cites Nerfies: Deformable neural radiance fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Nerfies: Deformable neural radiance fields

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.760503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6d4b3ace-5af2-4bb8-9770-3663262e6ce1 · outbound

This paper cites Perronnin and C.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Perronnin and C

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.750163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 096dbfc2-f381-4292-9fab-91338f024d02 · outbound

This paper cites Spatial cognition from egocentric video: Out of sight, not out of mind.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Spatial cognition from egocentric video: Out of sight, not out of mind

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.739524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4c4e0478-4629-4ed1-8de8-812e82ed68a2 · outbound

This paper cites D-nerf: Neural radiance fields for dynamic scenes.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos D-nerf: Neural radiance fields for dynamic scenes

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.729446Z

Source-reported events for the cited work

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Observation 0850a793-f42b-46d0-a394-2f43cb0f13de · outbound

This paper cites Langsplat: 3d language gaussian splatting.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Langsplat: 3d language gaussian splatting

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.718266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a86a223c-ac8b-42a3-91c5-9e928d1dce94 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Learning transferable visual models from natural language supervision

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.707268Z

Source-reported events for the cited work

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Observation dcf18d58-38bb-4986-87ea-b13ae3e8fcf9 · outbound

This paper cites Freeman, Fredo Durand, Joshua B.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Freeman, Fredo Durand, Joshua B

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.697665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 10c26b11-d60c-47d0-b80f-99c9c9102f0d · outbound

This paper cites Panoptic lifting for 3d scene understand- ing with neural fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Panoptic lifting for 3d scene understand- ing with neural fields

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.687249Z

Source-reported events for the cited work

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Observation 69d32895-acbc-4f8e-b756-b61be5e5f9ac · outbound

This paper cites Very deep con- volutional networks for large-scale image recognition.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Very deep con- volutional networks for large-scale image recognition

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.676090Z

Source-reported events for the cited work

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Observation 3d9f28cf-2a29-42fd-ae39-59eb871c4b34 · outbound

This paper cites Sivic and A.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Sivic and A

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.666450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d36bb915-e923-48f3-bd75-97c232765f87 · outbound

This paper cites NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:24:25.306078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 158bd12d-6cd1-4ebc-84a0-37a19d69d8d4 · outbound

This paper cites Dense point trajectories by gpu-accelerated large displace- ment optical flow.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Dense point trajectories by gpu-accelerated large displace- ment optical flow

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.656909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 61fe56d6-8765-44a8-970b-372c08fca40f · outbound

This paper cites Meaningful maps with object-oriented semantic mapping.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Meaningful maps with object-oriented semantic mapping

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.645675Z

Source-reported events for the cited work

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Observation 0dad3d60-c8eb-41a9-a578-d8b511eff63a · outbound

This paper cites Cnn-slam: Real-time dense monocular slam with learned depth prediction.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Cnn-slam: Real-time dense monocular slam with learned depth prediction

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.636221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 405b0706-b211-423c-abe4-6332cadfa262 · outbound

This paper cites Learning motion patterns in videos.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Learning motion patterns in videos

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.626970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b0d6aabe-0d24-4add-a430-73da3f17263a · outbound

This paper cites Training data-efficient image transformers & distillation through at- tention.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Training data-efficient image transformers & distillation through at- tention

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.617083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3bd2d079-069a-4c44-a174-99abd0b78142 · outbound

This paper cites Non-rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monoc- ular video.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Non-rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monoc- ular video

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.607927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5e06d032-dbd2-4b0c-af90-cdfa71f11783 · outbound

This paper cites NeuralDiff: Segmenting 3D objects that move in egocen- tric videos.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos NeuralDiff: Segmenting 3D objects that move in egocen- tric videos

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.597757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2f06cddc-9ee4-4f32-974b-41166ee50146 · outbound

This paper cites Neural Feature Fusion Fields: 3D distillation of self-supervised 2D image representation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Neural Feature Fusion Fields: 3D distillation of self-supervised 2D image representation

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.588094Z

Source-reported events for the cited work

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Observation a2517e1e-4b75-418e-a129-d7a98467da09 · outbound

This paper cites EPIC Fields: Marrying 3D Geometry and Video Understanding.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos EPIC Fields: Marrying 3D Geometry and Video Understanding

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.577737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3cfd68c3-504f-4628-b582-185c56c01547 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.568359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f834ade6-42f3-445c-bb9f-71251819728b · outbound

This paper cites In- cremental dense semantic stereo fusion for large-scale se- mantic scene reconstruction.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos In- cremental dense semantic stereo fusion for large-scale se- mantic scene reconstruction

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.558607Z

Source-reported events for the cited work

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Observation c6e47013-1e8f-497e-b376-3f4e4324ca60 · outbound

This paper cites NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-07T10:24:25.171231Z

Source-reported events for the cited work

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Observation ed7d20e1-c231-4370-8207-1304076daa64 · outbound

This paper cites DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T10:24:25.175087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fde2564-df89-47dc-8cf5-b55e84d9f639 · outbound

This paper cites Neural Trajectory Fields for Dynamic Novel View Synthesis.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Neural Trajectory Fields for Dynamic Novel View Synthesis

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T10:24:25.179030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 145845e1-6439-405e-911b-487dfe40fc05 · outbound

This paper cites Fourier PlenOctrees for dynamic radiance field rendering in real-time.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fourier PlenOctrees for dynamic radiance field rendering in real-time

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.547972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 29cdc2e1-3441-4cce-9878-e45aa9189dbd · outbound

This paper cites Zero-shot video object segmenta- tion via attentive graph neural networks.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Zero-shot video object segmenta- tion via attentive graph neural networks

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.537475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 33a635f0-9d9a-44df-80fe-f27a7cda5f19 · outbound

This paper cites an unresolved cited work.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:24:25.527933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c48ffbe5-da29-4db8-8212-23bd998afb9a · outbound

This paper cites Space-time neural irradiance fields for free-viewpoint video.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Space-time neural irradiance fields for free-viewpoint video

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.517574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3333c5db-6fb5-486a-bddd-f69bbdfca6c6 · outbound

This paper cites Object discovery in videos as foreground motion clus- tering.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Object discovery in videos as foreground motion clus- tering

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.508497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 392a08f6-cfa2-4012-9465-0f7aca7b7a36 · outbound

This paper cites Fig-nerf: Figure-ground neural radi- ance fields for 3d object category modelling.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fig-nerf: Figure-ground neural radi- ance fields for 3d object category modelling

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.498992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d83da0fe-6c48-4304-937e-e594c83c94ed · outbound

This paper cites Segmenting moving objects via an object-centric layered representation.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Segmenting moving objects via an object-centric layered representation

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.488788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8f317725-24bb-4523-b83f-370912356525 · outbound

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

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Self-supervised video object segmen- tation by motion grouping

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.478928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1ca9139-edb6-4a6e-ac59-a34c7704bbe5 · outbound

This paper cites Learning to segment rigid motions from two frames.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Learning to segment rigid motions from two frames

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.469326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7ee0a33e-ff55-40d6-841f-d2af3c3f046c · outbound

This paper cites Novel view synthesis of dynamic scenes with globally coherent depths from a monocular camera.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Novel view synthesis of dynamic scenes with globally coherent depths from a monocular camera

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.458694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fadf9500-e6c0-4c58-bde2-dca530db5bb6 · outbound

This paper cites Unsuper- vised discovery of object radiance fields.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Unsuper- vised discovery of object radiance fields

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.448154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 05965a7b-999e-4df4-95f5-98a87d514d83 · outbound

This paper cites Star: Self-supervised tracking and reconstruc- tion of rigid objects in motion with neural rendering.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Star: Self-supervised tracking and reconstruc- tion of rigid objects in motion with neural rendering

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.437745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1cbf51f3-fa00-4eec-a2c3-7b958283e69e · outbound

This paper cites Motion segmentation: A review.Artificial Intelligence Research and Development, pages 398–407, 2008.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Motion segmentation: A review.Artificial Intelligence Research and Development, pages 398–407, 2008

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.427780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f6e2ca73-5035-4ff6-af87-016822f0085b · outbound

This paper cites Fine-grained egocentric hand-object segmentation: Dataset, model, and applications.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Fine-grained egocentric hand-object segmentation: Dataset, model, and applications

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.418233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d11bccfc-2338-4dfb-93f5-12cc33462b9f · outbound

This paper cites Nerflets: Local radiance fields for efficient structure-aware 3d scene representation from 2d supervision.

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos Nerflets: Local radiance fields for efficient structure-aware 3d scene representation from 2d supervision

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:24:25.407514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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