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Paper Citation Record · LEDGER

On Moving Object Segmentation from Monocular Video with Transformers

As of 19 August 2026, this Paper Citation Record lists 100 of 110 outbound references and 1 inbound Pith citation observation for arXiv:2411.19141.

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

pith.paper-citation-record.v1
2411.19141 v1

Coverage vector

measured 100 of 110 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:32:37.728788Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:08:22.965713Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T00:08:24.618390Z

Reference resolution

100 of 110 outbound references displayed

  • verified exact7
  • verified fuzzy37
  • unresolved56
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e354dddc-a16b-42e4-bcca-b6cf9bacedcb · outbound

This paper cites A database and eval- uation methodology for optical flow.

On Moving Object Segmentation from Monocular Video with Transformers A database and eval- uation methodology for optical flow

Reference 1

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Observation 01c3951e-38f7-4830-9ebc-1e1c66bffcd5 · outbound

This paper cites Multimodal machine learning: A survey and tax- onomy.

On Moving Object Segmentation from Monocular Video with Transformers Multimodal machine learning: A survey and tax- onomy

Reference 2

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Observation 40744b64-0b69-4a9a-8834-06cbb247c495 · outbound

This paper cites Discovering objects that can move.

On Moving Object Segmentation from Monocular Video with Transformers Discovering objects that can move

Reference 3

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Observation 1de58df1-d97d-4373-a042-f96c53d89047 · outbound

This paper cites Object Discovery from Motion-Guided Tokens.

On Moving Object Segmentation from Monocular Video with Transformers Object Discovery from Motion-Guided Tokens

Reference 4

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Observation 5b5a29ad-c7e7-4593-a359-ba8648b80b1c · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers It’s moving! a prob- abilistic model for causal motion segmentation in moving camera videos

Reference 5

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Observation f4510415-8dac-4aeb-b0b6-920e42714f8d · outbound

This paper cites Moa-net: self-supervised motion segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Moa-net: self-supervised motion segmentation

Reference 6

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Observation 4df7e6d2-3c8b-41f3-9578-f68512eb81c9 · outbound

This paper cites The best of both worlds: Combining cnns and geometric constraints for hierarchical motion seg- mentation.

On Moving Object Segmentation from Monocular Video with Transformers The best of both worlds: Combining cnns and geometric constraints for hierarchical motion seg- mentation

Reference 7

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Observation 2c01f469-f3a4-4f58-925c-f06da2dfeb65 · outbound

This paper cites Neural-guided ransac: Learning where to sample model hypotheses.

On Moving Object Segmentation from Monocular Video with Transformers Neural-guided ransac: Learning where to sample model hypotheses

Reference 8

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Observation 1d9f6e82-ab23-441e-b6d0-582bcd1fa2f2 · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers Object segmentation by long term analysis of point trajectories

Reference 9

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Observation 05cf7fba-0f1b-4e21-a31d-e000d500f5e4 · outbound

This paper cites A naturalistic open source movie for opti- cal flow evaluation.

On Moving Object Segmentation from Monocular Video with Transformers A naturalistic open source movie for opti- cal flow evaluation

Reference 10

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Observation c2d42435-3e3a-4148-9930-8d6c528b5982 · outbound

This paper cites Virtual KITTI 2.

On Moving Object Segmentation from Monocular Video with Transformers Virtual KITTI 2

Reference 11

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Observation 294a9137-97d3-474f-9450-4d9bcf7c0659 · outbound

This paper cites End-to- end object detection with transformers.

On Moving Object Segmentation from Monocular Video with Transformers End-to- end object detection with transformers

Reference 12

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Observation 9b7f07e3-187b-4d48-af99-2b7bb02a8ce6 · outbound

This paper cites Mask2Former for Video Instance Segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Mask2Former for Video Instance Segmentation

Reference 13

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Observation 92acb01c-87c2-47ed-89c1-575190c07513 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Masked-attention mask transformer for universal image segmentation

Reference 14

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Observation 62326d37-3af9-4914-a33e-bc3d0e322c3a · outbound

This paper cites Per- pixel classification is not all you need for semantic segmen- tation.

On Moving Object Segmentation from Monocular Video with Transformers Per- pixel classification is not all you need for semantic segmen- tation

Reference 15

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Observation 5a6de8cf-bfb5-4af1-b805-d5d20dd4f4a3 · outbound

This paper cites Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion.

On Moving Object Segmentation from Monocular Video with Transformers Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion

Reference 16

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Observation 059c4a10-0f66-4db6-85b0-6abdd8af931b · outbound

This paper cites Robust estimation of a multi-layered motion representation.

On Moving Object Segmentation from Monocular Video with Transformers Robust estimation of a multi-layered motion representation

Reference 17

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Observation c0ad6966-0444-448c-b2f9-1fec7a59280f · outbound

This paper cites To- wards segmenting anything that moves.

On Moving Object Segmentation from Monocular Video with Transformers To- wards segmenting anything that moves

Reference 18

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Observation 81428128-be03-4680-a99a-26ad074920db · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers Fusion- seg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos

Reference 19

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Observation 787c6cff-e2c5-47ae-8250-6e1716dbbc41 · outbound

This paper cites Savi++: Towards end-to-end object-centric learning from real-world videos.

On Moving Object Segmentation from Monocular Video with Transformers Savi++: Towards end-to-end object-centric learning from real-world videos

Reference 20

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Observation b0f5018b-2d87-46b9-949b-65eeb4d2cef7 · outbound

This paper cites Detection free track- ing: Exploiting motion and topology for segmenting and tracking under entanglement.

On Moving Object Segmentation from Monocular Video with Transformers Detection free track- ing: Exploiting motion and topology for segmenting and tracking under entanglement

Reference 21

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Observation b206cd41-1254-4ec4-bc77-c6d52d6b5e38 · outbound

This paper cites Vision meets robotics: The kitti dataset.

On Moving Object Segmentation from Monocular Video with Transformers Vision meets robotics: The kitti dataset

Reference 22

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Observation 2304116d-a5a5-49d8-8840-6245210677c1 · outbound

This paper cites Separate visual pathways for perception and action.Trends in neurosciences, 15(1):20–25, 1992.

On Moving Object Segmentation from Monocular Video with Transformers Separate visual pathways for perception and action.Trends in neurosciences, 15(1):20–25, 1992

Reference 23

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Observation 8219b9ad-b8d8-4852-99ec-2cd6be968a83 · outbound

This paper cites In defense of the eight-point algorithm.

On Moving Object Segmentation from Monocular Video with Transformers In defense of the eight-point algorithm

Reference 24

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Observation 5c3c8779-0c55-4b82-b84c-6a36544002bc · outbound

This paper cites Mask r-cnn.

On Moving Object Segmentation from Monocular Video with Transformers Mask r-cnn

Reference 25

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Observation e0986797-2287-48ac-b24c-d93174abefef · outbound

This paper cites Deep residual learning for image recognition.

On Moving Object Segmentation from Monocular Video with Transformers Deep residual learning for image recognition

Reference 26

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Observation 8dc1c3ab-b247-4930-a03b-3c08efc866ce · outbound

This paper cites VITA: Video Instance Segmentation via Object Token Association.

On Moving Object Segmentation from Monocular Video with Transformers VITA: Video Instance Segmentation via Object Token Association

Reference 27

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Observation 73bd43a9-9bde-47a5-b048-833c3e79d9a8 · outbound

This paper cites Detect- ing and tracking multiple moving objects using temporal in- tegration.

On Moving Object Segmentation from Monocular Video with Transformers Detect- ing and tracking multiple moving objects using temporal in- tegration

Reference 28

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Observation 1ba3e123-40f2-402f-ad18-25f5b9d71b27 · outbound

This paper cites Pixel Objectness.

On Moving Object Segmentation from Monocular Video with Transformers Pixel Objectness

Reference 29

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Observation 7072606c-dd25-4839-8f0c-af226f768159 · outbound

This paper cites Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns.

On Moving Object Segmentation from Monocular Video with Transformers Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns

Reference 30

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Observation 1012d6ef-9626-48bc-a258-bb67e9c9a1d1 · outbound

This paper cites Segment Anything.

On Moving Object Segmentation from Monocular Video with Transformers Segment Anything

Reference 31

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Observation 5ad277c0-7fde-467d-9cac-e655d605b200 · outbound

This paper cites Ro- bust consistent video depth estimation.

On Moving Object Segmentation from Monocular Video with Transformers Ro- bust consistent video depth estimation

Reference 32

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Observation fb3be678-0311-49ae-949a-8568a5bf45e8 · outbound

This paper cites Betrayed by motion: Camouflaged object discovery via motion segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Betrayed by motion: Camouflaged object discovery via motion segmentation

Reference 33

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Observation a8bf3359-b682-455e-9bd8-d01748b99e45 · outbound

This paper cites Microsoft coco: Common objects in context.

On Moving Object Segmentation from Monocular Video with Transformers Microsoft coco: Common objects in context

Reference 34

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Observation 9c4ee25f-65bd-4288-814a-cc78ad6682dd · outbound

This paper cites The emergence of objectness: Learning zero-shot segmentation from videos.

On Moving Object Segmentation from Monocular Video with Transformers The emergence of objectness: Learning zero-shot segmentation from videos

Reference 35

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Observation d3348d61-3a1d-4fd8-a707-71a788fcb563 · outbound

This paper cites Prismer: A Vision-Language Model with Multi-Task Experts.

On Moving Object Segmentation from Monocular Video with Transformers Prismer: A Vision-Language Model with Multi-Task Experts

Reference 36

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Observation c5fdf2c6-b715-4eb9-8d76-6a9ca0ae660a · outbound

This paper cites Robust Dynamic Radiance Fields.

On Moving Object Segmentation from Monocular Video with Transformers Robust Dynamic Radiance Fields

Reference 37

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Observation b4c68f6b-4172-4f6e-a71c-98044a295fc2 · outbound

This paper cites Decoupled Weight Decay Regularization.

On Moving Object Segmentation from Monocular Video with Transformers Decoupled Weight Decay Regularization

Reference 38

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Observation 4669168a-b781-4465-bae0-243233d85f9a · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks

Reference 39

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.450305Z digest=sha256:7346bf4ec0345f84fa44c42ca101ea62be4df2d9bdf1a3d897c0eec07f4c2f3b

Observation 731f145b-bc72-4022-99a1-7a87429f432c · outbound

This paper cites Learning rigidity in dynamic scenes with a moving camera for 3d motion field estimation.

On Moving Object Segmentation from Monocular Video with Transformers Learning rigidity in dynamic scenes with a moving camera for 3d motion field estimation

Reference 40

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.454624Z digest=sha256:aa71192466d6b3d5a454a711c300e72350b0b0fa0dbc55830b6e7e9bf823efb1

Observation b232e6bf-18ec-450e-beeb-75ee47655730 · outbound

This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.

On Moving Object Segmentation from Monocular Video with Transformers A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 41

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.458901Z digest=sha256:4ce6e7cd82da1e756b47a9ad6f3c107f5e92743a0c455b65d891e0e9024968ae

Observation 326a60e8-cb7b-44f8-b508-aa56abee0f06 · outbound

This paper cites MODETR: Moving Object Detection with Transformers.

On Moving Object Segmentation from Monocular Video with Transformers MODETR: Moving Object Detection with Transformers

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-12T10:32:37.930640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.462995Z digest=sha256:6101d53e1fd8cb3b7b7299925c6ae7590ed29b57ffa187a03913b1b83f2c1f33

Observation 453fb021-4299-47bf-8601-a6abdee06304 · outbound

This paper cites Attention bottlenecks for multimodal fusion.

On Moving Object Segmentation from Monocular Video with Transformers Attention bottlenecks for multimodal fusion

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:39.016890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.467839Z digest=sha256:79f9ff24e095f09314578e65a2b26756e28e527da7a5667be24e3f96b572a466

Observation 60be7bf1-9ce7-49ab-a293-1b8dbb343198 · outbound

This paper cites Monocular arbitrary moving object discovery and segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Monocular arbitrary moving object discovery and segmentation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:39.002518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.472263Z digest=sha256:780909801d7c2fe69d722b89390e6fb4001c7112a200bb593fb50ec129b4d7db

Observation 667dd17e-e721-4451-a81a-22d5bfda6a1e · outbound

This paper cites Segmenta- tion of moving objects by long term video analysis.

On Moving Object Segmentation from Monocular Video with Transformers Segmenta- tion of moving objects by long term video analysis

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.987641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.476708Z digest=sha256:825e3a680b1816f0032c0455b22d05b8d98344c3da8a15f300e1cdf7ab3c453c

Observation 0894bd8e-3972-409a-9951-431aa8745db0 · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

On Moving Object Segmentation from Monocular Video with Transformers The 2017 DAVIS Challenge on Video Object Segmentation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.481185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.481185Z digest=sha256:fd7040e09fc214416557f12aa3b781a0cc81b6fce89ed648b6df918c8d2abaaf

Observation bbc061a1-fe44-4aa9-844f-109a20575e37 · outbound

This paper cites Vi- sion transformers for dense prediction.

On Moving Object Segmentation from Monocular Video with Transformers Vi- sion transformers for dense prediction

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.971564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.485790Z digest=sha256:a93627cd68346870aa22d5848ff6c5d6d7f98235013cce7a453569a844fc2f89

Observation e0662398-37e6-443b-b870-4af49785ad53 · outbound

This paper cites Optical flow estima- tion using a spatial pyramid network.

On Moving Object Segmentation from Monocular Video with Transformers Optical flow estima- tion using a spatial pyramid network

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.954955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.490160Z digest=sha256:2f84b96cc865dc2faa5fd92914cbcb8269b9a87f272bb24316367816c7dff1c9

Observation ca6fcb5c-c782-40d5-8432-de05571f9a15 · outbound

This paper cites Competitive collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Competitive collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.940187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.494414Z digest=sha256:288b0ee92f380dbe21bb326875f8c1c235379bada24281826460bdc7cf22d548

Observation 0ed0ee7b-a9a8-4c0d-bd3b-14b3e403fc70 · outbound

This paper cites Imagenet large scale visual recognition challenge.

On Moving Object Segmentation from Monocular Video with Transformers Imagenet large scale visual recognition challenge

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.925946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.498649Z digest=sha256:78da79105b46b56559b2f727b03f38fccf88b73909821b6b660b3b9186fa0bf7

Observation d901064f-8e2b-487e-a558-5bbf7e3f5ac1 · outbound

This paper cites 3d geometry from planar parallax.

On Moving Object Segmentation from Monocular Video with Transformers 3d geometry from planar parallax

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.910835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.503010Z digest=sha256:af4f64b0f88b90461e30c9de5bebf4310b2c7aeadec3674448661e33514d8d66

Observation de952be5-f0f1-48f7-8bc7-1ffec8bd2a7f · outbound

This paper cites Motion segmentation and tracking using normalized cuts.

On Moving Object Segmentation from Monocular Video with Transformers Motion segmentation and tracking using normalized cuts

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.896045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.507555Z digest=sha256:6d7558420a5ac7e82c66d86b04859ad30cf43b11ebaab796a7b6968e5a071ba2

Observation 49bb4a90-6334-4bf3-9182-c425433cc29c · outbound

This paper cites Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos.

On Moving Object Segmentation from Monocular Video with Transformers Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.511789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.511789Z digest=sha256:2e011ee9dc241a9d80af230325e4475d0d7ec0d9fcdaca77381f584a29836b03

Observation 56f366b1-dd1d-48a3-9015-84ebf1be3b7c · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

On Moving Object Segmentation from Monocular Video with Transformers Raft: Recurrent all-pairs field transforms for optical flow

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.516354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.516354Z digest=sha256:ec2801d9aa3cc292b90431b4fba6fee93e3877613c353e58cef4e86048d415e9

Observation f4652124-1fc7-40fa-bd94-8df28ac5b7d1 · outbound

This paper cites Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.

On Moving Object Segmentation from Monocular Video with Transformers Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.872373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.520667Z digest=sha256:816b7ac79fa75efda6eec13ce01bea7be8aacd0357458cf1ba44adcc24223c01

Observation 90f85192-4862-4dbc-a517-90124948900f · outbound

This paper cites Raft-3d: Scene flow using rigid- motion embeddings.

On Moving Object Segmentation from Monocular Video with Transformers Raft-3d: Scene flow using rigid- motion embeddings

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.859144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.524861Z digest=sha256:a34d1cf48a2ac12c0d9f0d7da84fca8c1dbeadad359a5ef2dd210b0740909b55

Observation 7ff902b3-a5e3-4566-a9b5-919402460958 · outbound

This paper cites Learning video object segmentation with visual memory.

On Moving Object Segmentation from Monocular Video with Transformers Learning video object segmentation with visual memory

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.845757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.528993Z digest=sha256:9a80ea2de1307c68e3c1d90fa231d80da9af6eb816f2be1872e38ce27af86e3f

Observation 663cfe81-d924-40c1-9afb-de4a6e1a48d4 · outbound

This paper cites Geometric motion segmentation and model selection.

On Moving Object Segmentation from Monocular Video with Transformers Geometric motion segmentation and model selection

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.832368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.533735Z digest=sha256:5ab8a96d6ff27e17a9a756fba3a7a3930e6655eb9f40d4f2f7b7a896be13a368

Observation f795935e-965c-47a5-a8b9-770d546fc287 · outbound

This paper cites The problem of degeneracy in structure and motion recovery from uncalibrated image sequences.

On Moving Object Segmentation from Monocular Video with Transformers The problem of degeneracy in structure and motion recovery from uncalibrated image sequences

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.818739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.538318Z digest=sha256:1d4c4abf63c560cc1230e341cb513db7fd7a35eeaaf5bed77cdb6057c0eda029

Observation 87b559ba-e070-4cab-bab8-434ab81114ce · outbound

This paper cites Robust detection of degenerate configurations while estimat- ing the fundamental matrix.

On Moving Object Segmentation from Monocular Video with Transformers Robust detection of degenerate configurations while estimat- ing the fundamental matrix

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.804419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation c7c15914-55f3-412d-a7d3-ba8a23bcd663 · outbound

This paper cites A benchmark for the com- parison of 3-d motion segmentation algorithms.

On Moving Object Segmentation from Monocular Video with Transformers A benchmark for the com- parison of 3-d motion segmentation algorithms

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.789270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.546745Z digest=sha256:c1da3fa42a074d98217088359a3de9d26e231a24a9782da886aa6cf4f74359e5

Observation fb49ff0a-9e39-462e-8a6d-51f3567face7 · outbound

This paper cites Video segmentation via object flow.

On Moving Object Segmentation from Monocular Video with Transformers Video segmentation via object flow

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.774628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.551075Z digest=sha256:2c8daa23d73b68aaa749660243a674aa561621649c6d636c5a2c6bf477c3261e

Observation 0955197d-352d-4cfb-9aac-b82b85f43431 · outbound

This paper cites Attention is all you need.

On Moving Object Segmentation from Monocular Video with Transformers Attention is all you need

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.759667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.555561Z digest=sha256:fd6357aac018f896d680c506014c9c044678a5f4bc24467e1495c0484fa973f3

Observation 51b7b9bc-2c67-4f3b-8143-79641535d54f · outbound

This paper cites Motion segmentation with missing data using powerfactorization and gpca.

On Moving Object Segmentation from Monocular Video with Transformers Motion segmentation with missing data using powerfactorization and gpca

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.745486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.560417Z digest=sha256:f7b85b2f7b78cea05d68261b557e100f49b569367ad260d5fa07ffb325f26fb4

Observation d4e9eef3-01f7-4d47-ab00-e1ec0a37e856 · outbound

This paper cites Optimal segmentation of dynamic scenes from two perspective views.

On Moving Object Segmentation from Monocular Video with Transformers Optimal segmentation of dynamic scenes from two perspective views

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.729275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.564825Z digest=sha256:f23b25177c50164407b18c1310a86935094627e61c4be5079f3605811cf5baac

Observation 17587c03-9449-44f2-85a8-00fce0059248 · outbound

This paper cites SfM-Net: Learning of Structure and Motion from Video.

On Moving Object Segmentation from Monocular Video with Transformers SfM-Net: Learning of Structure and Motion from Video

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.569611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.569611Z digest=sha256:6d21bfb1ca4081673c5781517d019db6bca676c30a6b1e9673ae34ad5332f922

Observation 3947c5c2-168b-4874-bc04-b64d17a060ed · outbound

This paper cites Opti- cal flow in mostly rigid scenes.

On Moving Object Segmentation from Monocular Video with Transformers Opti- cal flow in mostly rigid scenes

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.714364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.574764Z digest=sha256:1e3feea8c1d681a34049c950f5e471ea44d10b124c62567f9d8c811df78742e5

Observation 70690591-e70a-4714-8ec3-bb74bfa7121e · outbound

This paper cites Object discovery in videos as foreground motion clustering.

On Moving Object Segmentation from Monocular Video with Transformers Object discovery in videos as foreground motion clustering

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.700334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.579153Z digest=sha256:8c4eccb904263237258249e04cd7a41f29ed5c8dfb0c856c9a4e715bc87f67f0

Observation 10794445-aa19-4c26-9d76-3f81f0735ebd · outbound

This paper cites Segment- ing moving objects via an object-centric layered representa- tion.

On Moving Object Segmentation from Monocular Video with Transformers Segment- ing moving objects via an object-centric layered representa- tion

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.685555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.583701Z digest=sha256:b96848c870472c89c266161a9e929c5dd3cbf32b52f77c6852f4e15e4a13797c

Observation 2d832b65-e46a-4a46-9526-58ff39758aed · outbound

This paper cites Unifying Flow, Stereo and Depth Estimation.

On Moving Object Segmentation from Monocular Video with Transformers Unifying Flow, Stereo and Depth Estimation

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.588260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.588260Z digest=sha256:093d9bf76eec3f72b5727cbe2952f76b27def0fe0ef4c8e54f4f962a7551706d

Observation 47d29376-93dd-43c2-a576-5128796cb89d · outbound

This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.

On Moving Object Segmentation from Monocular Video with Transformers YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.592880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.592880Z digest=sha256:7d7d9a5f9c5c967af7be1d769bf2a55a991111c5bed31ce36c1602822bc28380

Observation d93c54a1-c045-45cb-95fd-1b2747f9e637 · outbound

This paper cites 3d rigid mo- tion segmentation with mixed and unknown number of mod- els.

On Moving Object Segmentation from Monocular Video with Transformers 3d rigid mo- tion segmentation with mixed and unknown number of mod- els

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.671433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.597731Z digest=sha256:eb1cfcdd4fd182d94e72aef6dda24c6ac81cab211ae0a21adc5194dd7fd9818f

Observation caa11949-00e0-43ee-ae3f-8aaa5e5315cd · outbound

This paper cites A general framework for motion segmentation: Independent, articulated, rigid, non- rigid, degenerate and non-degenerate.

On Moving Object Segmentation from Monocular Video with Transformers A general framework for motion segmentation: Independent, articulated, rigid, non- rigid, degenerate and non-degenerate

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.656961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.602084Z digest=sha256:0099a10f267394ef65014679710fe6cc7b94c803c78331482142378f17f998e3

Observation befbe4b6-6d95-4136-b4e9-c5d515a44f32 · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers Self-supervised video object segmentation by motion grouping

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-12T10:32:37.606704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:32:37.606704Z digest=sha256:e14b60e7e6493702cd7ee49612b5fa1b342d419920deaff735f15915204482cb

Observation 491035f8-0840-43a1-b254-c9f74fd67a62 · outbound

This paper cites Upgrading optical flow to 3d scene flow through optical expansion.

On Moving Object Segmentation from Monocular Video with Transformers Upgrading optical flow to 3d scene flow through optical expansion

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:32:38.633258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8b54f693-ad83-4876-aaba-958415b4cac7 · outbound

This paper cites Learning to seg- ment rigid motions from two frames.

On Moving Object Segmentation from Monocular Video with Transformers Learning to seg- ment rigid motions from two frames

Reference 76

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8f32864f-66d0-41b4-8361-96d72f9a6108 · outbound

This paper cites Video instance seg- mentation.

On Moving Object Segmentation from Monocular Video with Transformers Video instance seg- mentation

Reference 77

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 46e297c2-0bcb-491e-9bbe-a09c8cd7770d · outbound

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

On Moving Object Segmentation from Monocular Video with Transformers Unsupervised moving object detection via contextual information separation

Reference 78

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d3732622-481c-4a93-b9be-2f61be902603 · outbound

This paper cites Every pixel counts: Unsupervised geometry learn- ing with holistic 3d motion understanding.

On Moving Object Segmentation from Monocular Video with Transformers Every pixel counts: Unsupervised geometry learn- ing with holistic 3d motion understanding

Reference 79

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d7110c72-0b88-4274-ac0a-f8ee7351dd17 · outbound

This paper cites Detecting motion regions in the presence of a strong parallax from a moving camera by multiview geometric con- straints.

On Moving Object Segmentation from Monocular Video with Transformers Detecting motion regions in the presence of a strong parallax from a moving camera by multiview geometric con- straints

Reference 80

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 828cc112-0d98-4747-be92-204f526d0fb4 · outbound

This paper cites Consistent depth of moving objects in video.

On Moving Object Segmentation from Monocular Video with Transformers Consistent depth of moving objects in video

Reference 81

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 63d314c7-3787-4f0d-976d-934cf618654c · outbound

This paper cites Particlesfm: Exploiting dense point trajecto- ries for localizing moving cameras in the wild.

On Moving Object Segmentation from Monocular Video with Transformers Particlesfm: Exploiting dense point trajecto- ries for localizing moving cameras in the wild

Reference 82

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6c4644ee-be0c-4de6-83dc-8e9d360c34b0 · outbound

This paper cites Motion-attentive transition for zero-shot video object segmentation.

On Moving Object Segmentation from Monocular Video with Transformers Motion-attentive transition for zero-shot video object segmentation

Reference 83

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b2bafb5d-b805-4003-b65f-e31e1c95cfdf · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

On Moving Object Segmentation from Monocular Video with Transformers Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 84

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d04424b4-f706-4b9d-bbb7-ed537bcff581 · outbound

This paper cites Segment Everything Everywhere All at Once.

On Moving Object Segmentation from Monocular Video with Transformers Segment Everything Everywhere All at Once

Reference 85

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0cf664ad-289c-44fc-a78d-59a72743a2a5 · outbound

This paper cites Placement in the Literature There is a vast amount of related literature on segmen- tation, motion segmentation, moving object discovery and unsupervised feature learning.

On Moving Object Segmentation from Monocular Video with Transformers Placement in the Literature There is a vast amount of related literature on segmen- tation, motion segmentation, moving object discovery and unsupervised feature learning

Reference 86

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d9548249-f171-4abb-860e-a7f5cb05c98a · outbound

This paper cites Training Details We follow a similar training setup as [14].

On Moving Object Segmentation from Monocular Video with Transformers Training Details We follow a similar training setup as [14]

Reference 87

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3b4b67b6-68dc-4237-b696-3565a41d4fcf · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 88

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3a329901-d827-40b9-b962-841bace319f2 · outbound

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On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 89

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation c4a221c6-01c7-4ca9-ae8b-3db0204987c5 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 90

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2149a768-852a-47e8-8355-dd55b01125d9 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 91

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 73e2ff9b-786c-41ea-9621-906f7110451f · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 92

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9eb75a08-6152-4326-b995-cb813c4772a8 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 93

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9f2b9f0b-bc5e-42f2-9e90-16fc32b08080 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 94

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 41e49781-6b8f-4618-99a0-ac18514b6107 · outbound

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On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 95

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e7752abb-8e95-4f97-9efe-c32e043d97ef · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 96

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation db4cbbb3-54e2-40b5-9e13-f71a2981b475 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 97

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 18dcf6e8-0af2-43ef-bc16-3e270d956408 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 98

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation becb8f46-0376-42c5-a576-3c10e4a20a37 · outbound

This paper cites an unresolved cited work.

On Moving Object Segmentation from Monocular Video with Transformers Unresolved cited work

Reference 99

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3965b985-9825-41fc-97d2-356fbeed0aaf · outbound

This paper cites Costs BS / IS ✗.

On Moving Object Segmentation from Monocular Video with Transformers Costs BS / IS ✗

Reference 100

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-12T10:32:37.728788Z digest=sha256:bbb2e6c250da65063a86ca10963a18760f033952c043da843add2b3efcad9759

Pith citing papers

Observation 181391c7-e4c7-4f0e-8e3f-77e358b139b5 · inbound

STAR-VLM: Spatiotemporal Grounding Vision-Language Models for Motion and Velocity Estimation via Automotive Radar Supervision cites this paper.

STAR-VLM: Spatiotemporal Grounding Vision-Language Models for Motion and Velocity Estimation via Automotive Radar Supervision On Moving Object Segmentation from Monocular Video with Transformers

Reference 29

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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