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Paper Citation Record · LEDGER

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction

As of 8 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 0 inbound Pith citation observations for arXiv:2607.16192.

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

pith.paper-citation-record.v1
2607.16192 v1

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:08:11.723353Z

measured 87 of 87 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

87 of 87 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved81
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d39d198-f022-4dfb-a2e2-1d4a6c753b96 · outbound

This paper cites Gibson.The Ecological Approach to Visual Perception.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Gibson.The Ecological Approach to Visual Perception

Reference 1

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source=pdf_text observed=2026-08-01T21:08:02.926217Z digest=sha256:3a9ac82003afcbdd60e219336fa5aa86ce9c44060465d81be06a2f32f1655865

Observation d03305c0-239c-434e-a55a-57363f14e8a7 · outbound

This paper cites MIT Press, Cambridge, MA, 1979.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction MIT Press, Cambridge, MA, 1979

Reference 2

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Observation bbd53c76-1089-4357-a1b9-ab23afc9f07b · outbound

This paper cites Battaglia, Jessica B.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Battaglia, Jessica B

Reference 3

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source=pdf_text observed=2026-08-01T21:08:03.065262Z digest=sha256:391fd7a9a808d71f791ac7949d469941d54f33cebdef423c843c0dd264691bf0

Observation d0e28455-666f-445c-abff-0edd9914eabd · outbound

This paper cites Rational imitation in preverbal infants.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Rational imitation in preverbal infants

Reference 4

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source=pdf_text observed=2026-08-01T21:08:03.205525Z digest=sha256:0b4d7d18ae9dd93fd25b9682ba5aba6f47638874ceb7f1f3bd13b1802b252d94

Observation 2d2c935f-c823-4426-a51b-c3b1b8deba94 · outbound

This paper cites MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction

Reference 5

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source=pdf_text observed=2026-08-01T21:08:03.318004Z digest=sha256:7dd1bbbbae2ab3559e51b14de4162da8028e7e4dc11c235264af5c1805ef0b20

Observation 8bda7ddf-e769-428a-b03a-0e6824903cce · outbound

This paper cites Generating 6DoF Object Manipulation Trajectories from Action Description in Egocentric Vision.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Generating 6DoF Object Manipulation Trajectories from Action Description in Egocentric Vision

Reference 6

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source=pdf_text observed=2026-08-01T21:08:03.385771Z digest=sha256:32c98431286e5ac1ca58c91feef543fe413f97e8d639581d303b9451869e8f9b

Observation 1cf48797-d72c-4276-9406-c87c7738e523 · outbound

This paper cites ObjectForesight: Predicting future 3d object trajectories from human videos.arXiv preprint arXiv:2601.05237,.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction ObjectForesight: Predicting future 3d object trajectories from human videos.arXiv preprint arXiv:2601.05237,

Reference 7

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source=pdf_text observed=2026-08-01T21:08:03.492409Z digest=sha256:4e5f71101d639d5c353a11c3691c21bef969577e170d541e10eaa5f19748de56

Observation c80709e4-a0dd-4dd1-99f0-f06e8c906c05 · outbound

This paper cites Track2Act: Predicting point tracks from internet videos enables generalizable robot manipulation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Track2Act: Predicting point tracks from internet videos enables generalizable robot manipulation

Reference 8

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source=pdf_text observed=2026-08-01T21:08:03.635971Z digest=sha256:55840588780e5f500833d6b8b9949530a51db7b71e81f2dcfb3606e9272903fa

Observation bce010d1-35c8-4f0b-86fa-a15beb351f7e · outbound

This paper cites Any-point trajectory modeling for policy learning.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Any-point trajectory modeling for policy learning

Reference 9

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source=pdf_text observed=2026-08-01T21:08:03.706598Z digest=sha256:a2409d72c6c2377a2c39a62adb5db820bcc91bea73e1055637dd1d22d36e708c

Observation 9690d49b-e4c6-466d-b566-0dadabbccf18 · outbound

This paper cites Motion tracks: A unified representation for human-robot transfer in few-shot imitation learning.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Motion tracks: A unified representation for human-robot transfer in few-shot imitation learning

Reference 10

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source=pdf_text observed=2026-08-01T21:08:03.861656Z digest=sha256:01a107e01e8bf72eadbe049647b9427b09fa910242a8dd2d5e0925a6e5235dae

Observation e64d958b-996c-4fcc-9cfe-ccb10ac21c48 · outbound

This paper cites TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking

Reference 11

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source=pdf_text observed=2026-08-01T21:08:03.956642Z digest=sha256:bc01a1af26a0f22a2712a0896f9115de9b6b1bf249e9d9054467fcb76958d76e

Observation 087b81c3-1dc9-4d99-ba17-7b733fff36da · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Wan: Open and Advanced Large-Scale Video Generative Models

Reference 12

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Observation 3f0398c3-181a-41c3-b9a5-97ec90990127 · outbound

This paper cites World Models.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction World Models

Reference 13

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Observation d9b9b770-c82c-46d0-8c57-c891333c70aa · outbound

This paper cites Deep visual foresight for planning robot motion.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Deep visual foresight for planning robot motion

Reference 14

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source=pdf_text observed=2026-08-01T21:08:04.319399Z digest=sha256:c2f745382578e42a27a09155158e51de895e8d1cceec86ec2e38e01a2d95e4c4

Observation c87fa03f-70e7-46f4-8821-70dae328a2a8 · outbound

This paper cites Decomposing motion and content for natural video sequence prediction.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Decomposing motion and content for natural video sequence prediction

Reference 15

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source=pdf_text observed=2026-08-01T21:08:04.476158Z digest=sha256:ebd46b8efd2b6999ad32a5dc585fb1584f56dbe70bc139291033d3b55da1cdcc

Observation 753e912b-c894-4b5d-9962-357c5d639f3b · outbound

This paper cites An uncertain future: Forecasting from static images using variational autoencoders.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction An uncertain future: Forecasting from static images using variational autoencoders

Reference 16

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Observation a50c7708-3445-4e27-839f-f57d9922ba80 · outbound

This paper cites Gen2Act: Human video generation in novel scenarios enables generalizable robot manipulation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Gen2Act: Human video generation in novel scenarios enables generalizable robot manipulation

Reference 17

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Observation 1100d987-5939-4465-b9b4-f12699bcbece · outbound

This paper cites Video prediction policy: A generalist robot policy with predictive visual representations.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Video prediction policy: A generalist robot policy with predictive visual representations

Reference 18

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Observation 7f9ff0f1-8422-46a8-be47-7dbe75bb07f2 · outbound

This paper cites Video Generators are Robot Policies.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Video Generators are Robot Policies

Reference 19

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source=pdf_text observed=2026-08-01T21:08:04.972434Z digest=sha256:8cde571b70a22b5ee63cff44865b2fa26cf5ffa5f57a08cf11d2d7f4064e573a

Observation 8e4f0d75-d026-45bd-97a7-bd898ba0f5c4 · outbound

This paper cites Learning latent action world models in the wild.arXiv preprint arXiv:2601.05230,.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Learning latent action world models in the wild.arXiv preprint arXiv:2601.05230,

Reference 20

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Observation 9ed41a93-fa35-4286-901f-ac6f8d820a08 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 21

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Observation 4b9539c2-08a6-45ce-b59c-5ae20fb9871b · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 22

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Observation 32141199-f808-498b-9cc5-f0bb2f6023c9 · outbound

This paper cites Contrastive learning of structured world models.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Contrastive learning of structured world models

Reference 23

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Observation 02b630b1-2d65-4c8a-b075-e9e626c7878b · outbound

This paper cites SomethingSomething.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction SomethingSomething

Reference 24

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Observation 1bbda2fb-e58b-4128-8d26-d3346919153a · outbound

This paper cites Doell, and Jason J.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Doell, and Jason J

Reference 25

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Observation 8cdc7013-fb8c-43fa-ad6a-df4845f3e0b4 · outbound

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MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

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Observation 473d728d-24be-4b5f-87cf-02ee5cfcb27b · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

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Observation 953f0aa9-b9fd-459b-ba01-e36412422fb6 · outbound

This paper cites Dream to con- trol: Learning behaviors by latent imagination.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Dream to con- trol: Learning behaviors by latent imagination

Reference 28

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Observation bd1e8057-cea0-43dd-baf6-d87a3ac50b93 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 29

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source=pdf_text observed=2026-08-01T21:08:05.980579Z digest=sha256:ddfbac85a6ed5020c13728181777136f584c0ad1810d22c75b7d5a87351e4bab

Observation 4a1824d8-df7d-4e9a-b31c-c7bb4249840b · outbound

This paper cites Human–object interaction prediction in videos through gaze following.Computer Vision and Image Understanding, 233: 103741, 2023.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Human–object interaction prediction in videos through gaze following.Computer Vision and Image Understanding, 233: 103741, 2023

Reference 30

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Observation 28f98bed-959a-4dfa-a104-25a34c397f0c · outbound

This paper cites ContactGrasp: Functional multi-finger grasp synthesis from contact.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction ContactGrasp: Functional multi-finger grasp synthesis from contact

Reference 31

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Observation f4b6d1d4-f3e4-4285-95bb-caece6d5123b · outbound

This paper cites Scaling egocentric vision: The EPIC-KITCHENS dataset.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Scaling egocentric vision: The EPIC-KITCHENS dataset

Reference 32

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Observation 6600dc5b-fb2b-45f6-be4f-83e9b0bfee58 · outbound

This paper cites Joint hand motion and interaction hotspots prediction from egocentric videos.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Joint hand motion and interaction hotspots prediction from egocentric videos

Reference 33

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Observation a96a30c3-7ded-4cbc-9596-7776ff9e10c2 · outbound

This paper cites Ego4D: Around the world in 3,000 hours of egocentric video.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Ego4D: Around the world in 3,000 hours of egocentric video

Reference 34

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Observation 9861203a-874f-4111-bbe6-da276283adea · outbound

This paper cites Newtonian image understanding: Unfolding the dynamics of objects in static images.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Newtonian image understanding: Unfolding the dynamics of objects in static images

Reference 35

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Observation 25f96095-8223-46c0-8564-fe4458022f59 · outbound

This paper cites Grounded human-object interaction hotspots from video.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Grounded human-object interaction hotspots from video

Reference 36

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Observation d35973f7-524c-441d-b48e-44a2322d0f3d · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 37

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source=pdf_text observed=2026-08-01T21:08:06.542986Z digest=sha256:afd666f0d60d08c8f10b510b93f3398674b0e255d5c9174c341b7eece526230c

Observation 77876ee3-c8f6-420f-bd4d-343a2f6197ff · outbound

This paper cites Human hands as probes for interactive object understanding.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Human hands as probes for interactive object understanding

Reference 38

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source=pdf_text observed=2026-08-01T21:08:06.187309Z digest=sha256:7cc5d56da805dd5810e131e509e87b9f65c7691a3019ac8b3d546a7865dcc659

Observation 89482c55-4d31-4fb9-8ee6-08a30eaafcdd · outbound

This paper cites HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction

Reference 39

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source=pdf_text observed=2026-08-01T21:08:06.701306Z digest=sha256:ebb78836a684740cd3b4931d26e8f153f46945ec3a7c12623b415c2aadecd995

Observation 1b0d3e2b-9ea3-4c8f-a196-90e97a5d8159 · outbound

This paper cites Guibas, Mustafa Mukadam, Abhinav Gupta, and Shubham Tulsiani.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Guibas, Mustafa Mukadam, Abhinav Gupta, and Shubham Tulsiani

Reference 40

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source=pdf_text observed=2026-08-01T21:08:06.350657Z digest=sha256:24e9f4181f6a6f0841f4f4f5422068924eac70a4d84ef47d5867cee1d33fd216

Observation 40f5bd1d-9f4e-44de-8485-c8dfc00899db · outbound

This paper cites Mask2Act: Predictive multi-object tracking as video pre- training for robot manipulation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Mask2Act: Predictive multi-object tracking as video pre- training for robot manipulation

Reference 41

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source=pdf_text observed=2026-08-01T21:08:06.862084Z digest=sha256:5e52c02bb37df1f527374530457274f7793c149ae3a41be1bc247174d28a4705

Observation 15ac6c39-325d-4f71-8259-117316dd7cce · outbound

This paper cites 3d hand shape and pose estimation from a single RGB image.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction 3d hand shape and pose estimation from a single RGB image

Reference 42

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source=pdf_text observed=2026-08-01T21:08:06.937012Z digest=sha256:1c78ed0780898ef4f68db18e72ea282873bc87914752d48969195bfaff6b48cd

Observation 67cc1d18-74fd-4728-86f7-c66bb7808793 · outbound

This paper cites Black, Ivan Laptev, and Cordelia Schmid.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Black, Ivan Laptev, and Cordelia Schmid

Reference 43

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source=pdf_text observed=2026-08-01T21:08:06.997853Z digest=sha256:c56b45695b69b39c8267d14190553d6fbc1f84bfea8f6b2181366f3da9260f68

Observation a11e4dc1-4bf6-415b-8744-3c91d1691522 · outbound

This paper cites Guide to the carnegie mellon university multimodal activity (CMU- MMAC) database.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Guide to the carnegie mellon university multimodal activity (CMU- MMAC) database

Reference 44

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source=pdf_text observed=2026-08-01T21:08:06.621031Z digest=sha256:b03e8b021e8786e5c0064dd4323d1b28fb1822b8f08633b1703286e7c24dd438

Observation 3220aa4f-8613-4118-85e8-fc111bbb4453 · outbound

This paper cites FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration

Reference 45

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source=pdf_text observed=2026-08-01T21:08:07.169924Z digest=sha256:9ea6fe67542588048320e7ef5fb62491377793eeba0617502c90a1d1cd9f8d56

Observation d9bdb4bc-e81e-437a-8366-c16a7e260967 · outbound

This paper cites Flowing from reasoning to motion: Learning 3d hand trajectory prediction from egocentric human interaction videos.arXiv preprint arXiv:2512.16907, 2025.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Flowing from reasoning to motion: Learning 3d hand trajectory prediction from egocentric human interaction videos.arXiv preprint arXiv:2512.16907, 2025

Reference 46

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source=pdf_text observed=2026-08-01T21:08:06.765398Z digest=sha256:4a1e4aa1badcd6a81eecf4bec68372259bddf050fe02f6ac75e2e3cc709993e3

Observation 1fe054e9-fb57-44f8-829e-1c20f51eed55 · outbound

This paper cites PVN3D: A deep point-wise 3d keypoints voting network for 6dof pose estimation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction PVN3D: A deep point-wise 3d keypoints voting network for 6dof pose estimation

Reference 47

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source=pdf_text observed=2026-08-01T21:08:07.512912Z digest=sha256:1dc04a6e50f7a22f1fb67e88aae414066d53b0fdb795f3735d944925793143e8

Observation faf6970f-f887-4b33-88b6-96d3a0ea3221 · outbound

This paper cites Segmentation-driven 6d object pose estimation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Segmentation-driven 6d object pose estimation

Reference 48

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source=pdf_text observed=2026-08-01T21:08:07.668258Z digest=sha256:9d1e91b970815cc3811df7f7c84342f4ab7833e38bbcf0b75399eb7031e62f1d

Observation d98d81c3-be80-42ac-9b5e-29ad52b51ad2 · outbound

This paper cites SSD-6D: Making RGB-based 3d detection and 6d pose estimation great again.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction SSD-6D: Making RGB-based 3d detection and 6d pose estimation great again

Reference 49

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source=pdf_text observed=2026-08-01T21:08:07.824655Z digest=sha256:6a1c7439bc16f205323ba5c97c5650587f461e3e2c1d94e4a10ef42e612cbfef

Observation ed9f48a8-f0cb-4d1e-a57b-8940e5e0bfde · outbound

This paper cites Hand pose estimation via latent 2.5d heatmap regression.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Hand pose estimation via latent 2.5d heatmap regression

Reference 50

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source=pdf_text observed=2026-08-01T21:08:07.013467Z digest=sha256:7ab95d37fd6b0a7c80e4d115bbaa422e2f10771a8baab177380215e7b594aee5

Observation 194c8f67-903d-4bc5-843f-52ea3333300a · outbound

This paper cites SAM 2: Segment anything in images and videos.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction SAM 2: Segment anything in images and videos

Reference 51

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source=pdf_text observed=2026-08-01T21:08:08.108094Z digest=sha256:aaf40f439056e3c22332fad868d6394cc7850e5dfa43d93872d5a47ef7d8bd10

Observation dcc1f61a-bf86-45de-acd4-d0d05a6e7958 · outbound

This paper cites Learning to estimate 3d hand pose from single RGB images.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Learning to estimate 3d hand pose from single RGB images

Reference 52

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T21:08:07.316576Z digest=sha256:47b8b2863497b3d69c7f42f6688c100cd8be9783d237eef73801fee7975b2c37

Observation cb77d25c-bb1b-41b1-af3d-7341aa9f23b9 · outbound

This paper cites SAM 3D: 3Dfy Anything in Images.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction SAM 3D: 3Dfy Anything in Images

Reference 53

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source=pdf_text observed=2026-08-01T21:08:08.479185Z digest=sha256:d1ac6980589ba825935c1bf0f93ce4668491d191048f19d8c3cdb974056b3125

Observation b8676e74-e36d-49b0-b586-145764dc2d84 · outbound

This paper cites Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks

Reference 54

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source=pdf_text observed=2026-08-01T21:08:08.666083Z digest=sha256:524d0ac6e2b929e8637aeb4dc72b8707988a9af281848de32350903f915adb11

Observation dcb1968e-f585-4a5f-b4fc-df833d9e205d · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Visual point cloud forecasting enables scalable autonomous driving

Reference 55

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source=pdf_text observed=2026-08-01T21:08:09.071412Z digest=sha256:c811edc48160f0c5f6fcc3e1c62babc00e2bbf2cb6d3399ca52f0234a33de084

Observation 2afc36e2-8916-407f-a0dd-8b9557e5cfc2 · outbound

This paper cites PoseCNN: A convo- lutional neural network for 6d object pose estimation in cluttered scenes.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction PoseCNN: A convo- lutional neural network for 6d object pose estimation in cluttered scenes

Reference 56

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source=pdf_text observed=2026-08-01T21:08:07.942149Z digest=sha256:610ba031a831579c0023e9706d3a0cf36140b1be9ad915923577829c50ce2bc1

Observation 4fc5edd6-1945-4d90-96e5-ff75231c0e07 · outbound

This paper cites ManipTrans: Efficient dexterousbimanualmanipulationtransferviaresiduallearning.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction ManipTrans: Efficient dexterousbimanualmanipulationtransferviaresiduallearning

Reference 57

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source=pdf_text observed=2026-08-01T21:08:09.493365Z digest=sha256:c24174ef3779c9b184de82fb9616d66e77e111a7930402ae57bcb08a285d0dcd

Observation 502a4ad2-0f4d-458c-8697-ea0593e37f38 · outbound

This paper cites Structured 3d latents for scalable and versatile 3d generation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Structured 3d latents for scalable and versatile 3d generation

Reference 58

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source=pdf_text observed=2026-08-01T21:08:08.328003Z digest=sha256:02f6ba2dcb110bb35888fef2d6df760b3c64bc486b953053b48eddaa79210405

Observation 3dbe438d-aa1a-46c2-81a9-1f624dfa8f43 · outbound

This paper cites World models for learn- ing dexterous hand-object interactions from human videos.arXiv preprint arXiv:2512.13644,.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction World models for learn- ing dexterous hand-object interactions from human videos.arXiv preprint arXiv:2512.13644,

Reference 59

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source=pdf_text observed=2026-08-01T21:08:09.950434Z digest=sha256:baaa4a9a501c35ace3c3cfe1312ebcc6674316d0ecde988b28f80661d9371008

Observation 46e02707-70f1-4da8-b826-125d87fe3ebe · outbound

This paper cites Qi, and Leonidas J.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Qi, and Leonidas J

Reference 60

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source=pdf_text observed=2026-08-01T21:08:10.208378Z digest=sha256:a8b55b77924d1be2b607254d73e06a18f34e852541fc108bd12ff9e929dd8f43

Observation 5dc331fd-2879-43ad-b8c8-0ca2850087af · outbound

This paper cites Harley, Yang You, Xinglong Sun, Yang Zheng, Nikhil Raghuraman, Yunqi Gu, Sheldon Liang, Wen-Hsuan Chu, Achal Dave, Suya You, Rares Ambrus, Katerina Fragkiadaki, and Leonidas J.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Harley, Yang You, Xinglong Sun, Yang Zheng, Nikhil Raghuraman, Yunqi Gu, Sheldon Liang, Wen-Hsuan Chu, Achal Dave, Suya You, Rares Ambrus, Katerina Fragkiadaki, and Leonidas J

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source=pdf_text observed=2026-08-01T21:08:10.378846Z digest=sha256:62299dc1c9c0c8fd9de164eb0f88270d7db3b7eb76ee64dfea1961d49db35f47

Observation dc4884ea-653d-4f14-8da4-9e7b9ec9ede5 · outbound

This paper cites ViP3D: End-to-end visual trajectory prediction via 3d agent queries.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction ViP3D: End-to-end visual trajectory prediction via 3d agent queries

Reference 63

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source=pdf_text observed=2026-08-01T21:08:09.331914Z digest=sha256:6eb2fefe9028dac7a412efcc28b5b27ee5d8d742a9dfd101f08995ccc7a79dbc

Observation 3a497286-20c1-4af7-8ded-d241fcc3674c · outbound

This paper cites DELTA: Dense efficient long-range 3d tracking for any video.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction DELTA: Dense efficient long-range 3d tracking for any video

Reference 64

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source=pdf_text observed=2026-08-01T21:08:10.583837Z digest=sha256:ca9f447a597721596b4049b4acb8d85a76a2f6e53afbe99ec0fe12e4812f7d12

Observation ee2324a4-746d-4784-92aa-399747a27aee · outbound

This paper cites PointWorld: Scaling 3d world models for in-the-wild robotic manipulation.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction PointWorld: Scaling 3d world models for in-the-wild robotic manipulation

Reference 65

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source=pdf_text observed=2026-08-01T21:08:09.689219Z digest=sha256:bdfe915b75292f5f9bd2b5405f70c00839ee546c5b34c1c7b0c54791a22787a0

Observation b8eef71c-872c-4323-ad24-6e9a93874599 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 66

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source=pdf_text observed=2026-08-01T21:08:10.736636Z digest=sha256:d945b5928f28ee7c3a2e92948f59c81675ff6a08019d38140f8041314d266f3b

Observation 22762334-5b6f-4e3a-814d-57776dd59222 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 67

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source=pdf_text observed=2026-08-01T21:08:10.084810Z digest=sha256:b109091399b1f9cd1e92e38c5e1d41e21fde068fe0575bada2c5d530445dae8f

Observation 9945e0b2-8aa4-4742-8f1b-2ab3d85d5b77 · outbound

This paper cites Rotary position embedding for vision transformer.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Rotary position embedding for vision transformer

Reference 68

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source=pdf_text observed=2026-08-01T21:08:10.885000Z digest=sha256:4ae2ff36e6428c75844bf4490e5877f8f4fe54d639e6c143ecbefff8f39bd20f

Observation 45d21f6d-d9e4-4841-98a2-8f6bac3fdb2f · outbound

This paper cites RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 69

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source=pdf_text observed=2026-08-01T21:08:10.959228Z digest=sha256:59fc18754a89af3026a19d6c7cbd8a49065eeebae310f98d2d1e47e4990b7682

Observation b384054c-23ba-4e3f-8b4a-7b90cd4f43d1 · outbound

This paper cites Forecasting motion in the wild.arXiv preprint arXiv:2604.01015, 2026.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Forecasting motion in the wild.arXiv preprint arXiv:2604.01015, 2026

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source=pdf_text observed=2026-08-01T21:08:11.020780Z digest=sha256:8fd433477c4b22578d3555bfc1f2df9183747ba0c17f385f9b148fa9ed3961a4

Observation 218eedf8-6a4e-47af-b1ce-64c29abedf4b · outbound

This paper cites CoTracker: It is better to track together.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction CoTracker: It is better to track together

Reference 71

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verified exact
doi, observed 2026-08-01T21:08:32.681179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-01T21:08:10.509167Z digest=sha256:acfb005be15df0d6dae92cead032abe864f6f8329a17cb05792ca4ea1d150ef1

Observation 29f1935a-8d90-4b9a-8ac9-c3402ed5817d · outbound

This paper cites Dex4d: Task-agnostic point track policy for sim-to-real dexterous manipulation.arXiv preprint arXiv:2602.15828, 2026.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Dex4d: Task-agnostic point track policy for sim-to-real dexterous manipulation.arXiv preprint arXiv:2602.15828, 2026

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source=pdf_text observed=2026-08-01T21:08:11.168088Z digest=sha256:81d56ffa7fe6ea313e55def4944f6ebaf09487f7250d660e6bef5972b4fd7666

Observation dab819f2-27b4-431b-a2f5-2b9340d0b476 · outbound

This paper cites SpatialTrackerV2: Advancing 3d point tracking with explicit camera motion.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction SpatialTrackerV2: Advancing 3d point tracking with explicit camera motion

Reference 73

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source=pdf_text observed=2026-08-01T21:08:10.659830Z digest=sha256:e4e30abc9a9159711863071cc9bb31be011921190d57beebd20e000ce8bd7095

Observation 0df9acc1-845c-4247-8e25-1e2ab0283843 · outbound

This paper cites Depth Anything 3: Recovering the Visual Space from Any Views.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Depth Anything 3: Recovering the Visual Space from Any Views

Reference 75

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source=pdf_text observed=2026-08-01T21:08:10.829759Z digest=sha256:de89bcdb06666f8dc7aced26df73d0867392be34cd001c801df6e43eaf98c8cf

Observation 2aabca53-94dc-459b-b35b-8a32fefaae46 · outbound

This paper cites Novaflow: Zero-shot manipulation via actionable flow from generated videos.arXiv preprint arXiv:2510.08568, 2025.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Novaflow: Zero-shot manipulation via actionable flow from generated videos.arXiv preprint arXiv:2510.08568, 2025

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Observation 225639f7-6d36-48ae-9fb9-93d6691cd78b · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 81

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Observation e0ff0579-802d-4d89-8adf-0d50cae0a32c · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 82

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Observation 1b81fa00-33dc-4cb1-8b1b-1c4f1e3e5ec9 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 83

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Observation 85254c77-8344-4712-8298-2d49a303b335 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 84

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source=pdf_text observed=2026-08-01T21:08:11.475358Z digest=sha256:a79308cd659e9c13b52e88af374afb671be570703024e9d5fa402c4e4183d6a7

Observation 64ddfc8a-ec61-479e-b968-9441e5b204aa · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 85

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source=pdf_text observed=2026-08-01T21:08:11.548643Z digest=sha256:18718b1184586b40d473516846844fbfdcf5453905a4857417511203ef67e0b6

Observation 6edb8e74-a3d3-43b1-bbd8-6c67248d4b81 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 86

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Observation 97f24870-0ae4-4162-b1ed-48869ff97e3e · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 87

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source=pdf_text observed=2026-08-01T21:08:11.674282Z digest=sha256:dd8b6cdc45331a24f6625af053e7303c19bd9e2b95af921dbf6b18df8e20a4c7

Observation 9737f7df-901c-4a8f-8d77-c0d90c9acfbb · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 88

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source=pdf_text observed=2026-08-01T21:08:11.723353Z digest=sha256:11bc7c2d6962210c4a9ff5619687498ed894a52accfd70ad8f1d535fa94a34d0

Observation 53b09f4e-3d7b-41bc-b8f2-9c61fe2a1288 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 2017

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source=pdf_text observed=2026-08-01T21:08:04.392981Z digest=sha256:9c2d4810dfb6b28070992727fb825b4d3251deee05961829e6d6d7ef23f7b6a0

Observation e4605b7f-e1b6-4231-afec-c042f6cc3452 · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 2022

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source=pdf_text observed=2026-08-01T21:08:08.839813Z digest=sha256:3c86763fd85b2489d0d77f901281a560d10994d3f32ea8f20cdc8d4f446d38d1

Observation 7de84400-49ce-4983-b129-bec74691297c · outbound

This paper cites an unresolved cited work.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Unresolved cited work

Reference 2024

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source=pdf_text observed=2026-08-01T21:08:03.774833Z digest=sha256:6a23f486d7b1d7b5c0a287739a59ae7b55f393eba92c9366cc7e4f370b5d32df

Observation 9ca762a5-3b80-460d-8ae4-1e7ab71e8bfd · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction Wan: Open and Advanced Large-Scale Video Generative Models

Reference 2025

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source=pdf_text observed=2026-08-01T21:08:04.131033Z digest=sha256:611c05d3a44729382965215a99d7089921f3d4bd5afd12a5a89000d461974bbd

Observation cea0f0cd-1890-4e9b-9bfa-af71316ad47c · outbound

This paper cites 12 MotionForesight Brains, Bots, and Behavior Lab.

MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction 12 MotionForesight Brains, Bots, and Behavior Lab

Reference 2026

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source=pdf_text observed=2026-08-01T21:08:03.567786Z digest=sha256:54933e5d8b11e078f4fcf518a14514f5ab895ec1816aee04d1244ef6be9c7a26

Pith citing papers

No inbound Pith citation observations are available.