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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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=sha256:20595f296e12ef1e8283afe3fa4853a3780c44e9331bece01cf5a06d2b918982

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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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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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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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=sha256:4a3540e1a97470169a1ff89ed61d34e9a7771effa64e5e5dd5b453df31b242b8

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:a8b2aaabddf64e4c0150fb2fd4c06ed273a57a2d202a5f0bac3cd6e4d6b7917d

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=sha256:1aab57b62e9973b878941db2797e09696a1a9f9595ae803a918a806150cff7e1

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=sha256:5affd2dfccf6ba78377075ee1a074299bf3e7a2ed0801a3aafe66be1cede407e

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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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=sha256:1640465853f538852087f8745165675abcec1363c2eb741c55369775d8cc353a

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=sha256:81029047e6ad00b52a5dd6c58c05ed708dec4f84443c846d8a7eb3afadd41a80

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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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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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

Reference 27

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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:dcaa31259004217e2ff7f4b012632780ee94c4fc786b529b2e60e6f3f36c521f

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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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=sha256:0c967fc9f58b95584d18272e32de089855b4c7d120068969f68781c86fa271fc

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=sha256:24f0c8da245fc13a051458f1c01a51123281d1b9db08355d05620e0cc408ba27

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=sha256:9f189936444a36dfe710c0decd8582cb69fa007d51436ce4f2eb3cc98231739c

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=sha256:5fa4ce5514bea5e043f9ea79b9fa542a0b7fac019f0c2a9d9512f60ab4bb5e52

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=sha256:1a374d257ec7311edc4fb79d3d8294a6e450274e2bf94b60d765c3d9920c6bc8

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=sha256:597333844130d281d00bbf65c1b1d99a74f774a9723d46a3209e875b205eed0b

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:d48bf3e12b48cf68bf2b15d994ab8ebc50c76bab72775d9af1068daa761cd997

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=sha256:91d272f323a0b53cf03e3fceb175ac659f980882b9a995713dbb1b8e70650679

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=sha256:0ebf0b500128337a66f6440ba11b94421a009f6a89711d4b6c771bb4af149251

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:cb8393c68933489a2b8391e7939d042e6cb4f51a59593c915669dedbdb885812

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=sha256:8226d732338a461371660102e42675913a7225436f05403e70a76f4b3486583d

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=sha256:9ffd443f6160ba47f99da0657ba44db10038253b3a65946720aab6d087b3fde8

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=sha256:4aa10b7e7f1e8f5fe882a492bc0636a172521a5f551935ab721430fc9abd44d5

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:de2960c4d004d063c3a3307e5904fcbde89bc6b3ef9266ad4a8da84ab1e60372

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=pdf_text observed=2026-08-01T21:08:07.316576Z digest=sha256:4c9262088762b49ce94de2fe04de0ce3e150b6acf7f95d5ddf0aa7f035759515

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=sha256:018be781b81c1bc3ed0b609f6d0f474abe349b57d192ecfa9c2c509ff42c6067

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=sha256:3f7ad4f4b1112830c34959210bee011748bde802fa2192fc27e5282000c4a32c

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:f3b9ed731d0010cb37ce7d7a7455e80b468d831c22edd5b507b2fbf69f0271de

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=sha256:367648916b4c3f010badc98ccb7acb4b904b758d741a29e40bd1b7323715579d

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=sha256:180e9efa0da38445acefd694888239ec42e99bfd108fe264c04cda79d50376f9

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=sha256:7732d10847671ffc317509aa6cce13c3603089c76a4e466e9088b877a009beed

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=sha256:7c6eb2d52cccca5755366e863bb37ef8d33ab1677632eb0e4eaf9d072696c90c

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:af36f24c2ed30e33c1d4fa918a2f4ac688cc58c096cdedb9302114aed2761571

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:b28118c38a1b7f0d4c4fe5cd5f0c1180a3dff16043b7da421f7688f6e383a086

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=sha256:87854abde6f338ab9dca88436f57448d3bb48b8ae30ee7240b1a43da59dc43ff

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=sha256:99d3ba54c19ac4c120e0e55f11f7b6eabac4cad3c206b3c8b09a0eb3e939704a

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=sha256:98e8e416750666810be328142b13e4a88129cb072f9d9411ecac0c8f4bc9fbf4

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:e0bc4d931c80e2272102ce529b8fd81e7153873ca9086b86ea925157d594406f

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:dc020d1b858f72bb9cb255585504bd299a3238a4e57d3e5a2f92f5211bc32d8b

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:d68e6419035fc47c235eebe28ca86a18c8c470bc731a0173ed73323d80a2b7fb

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=sha256:83aa5d7b0c0af9a4997f5cb2cb06ca4f4a6697901172385c9b8868a96da38860

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=sha256:5c7ca84961aae31dec2736a984f9c78f401ba1371d24548eb96f3ba044b50a3e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-01T21:08:10.509167Z digest=sha256:90c2744b74853cc013e747f779149f41c8a491f1f112367e9d0f8d366b7c3cc4

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:e1146dfb56131b62846625acc70cb136c866b5ff264eba0cfbc30873d9afbd9e

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:e82f7f7201d2115c43d9a6a06cef3d88b70faf63555f79fb1246f04429b7ba3d

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=sha256:12975d057bb151ce279a349036cfcc166e7a843f628d485c57fb96f3bd11a09a

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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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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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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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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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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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=sha256:4e87ad008cb2824b49800a6974a60cf6dd369ee28ccc6bab0e3ed3b2297d3ae9

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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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=sha256:2a5b877a973fb86f0b25f03b0b882566d04b651e9dc3f0ba8f826e6088440a91

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=sha256:8c6c35ae6ba24103d4376f6bdea8718b9ba4a1ff4be46ec0405fac9f5e01cc92

Pith citing papers

No inbound Pith citation observations are available.