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Paper Citation Record · LEDGER

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling

As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:1908.07214.

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

pith.paper-citation-record.v1
1908.07214 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:27:23.729103Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:24:38.406290Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T17:24:38.924220Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy42
  • unresolved9
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c134652e-4abf-4df5-9670-a8d1e2f808b9 · outbound

This paper cites A deep learning framework for character motion synthesis and editing,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling A deep learning framework for character motion synthesis and editing,

Reference 1

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Source-reported events for the cited work

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

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Observation 9d98986e-ad4e-4218-b37c-63a38f614f40 · outbound

This paper cites Motion graphs,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Motion graphs,

Reference 2

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verified fuzzy
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Source-reported events for the cited work

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

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Observation fcc9f833-2245-4493-a925-aacd415017fa · outbound

This paper cites Modeling human motion using binary latent variables,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Modeling human motion using binary latent variables,

Reference 3

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verified fuzzy
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Source-reported events for the cited work

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

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Observation ef6e2705-6f43-4cf6-8bf6-a4fc46dc0cee · outbound

This paper cites Motion graphs++: a compact generative model for semantic motion analysis and synthesis,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Motion graphs++: a compact generative model for semantic motion analysis and synthesis,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 4ae4e2fb-7805-479a-a8a7-c07f5be598ed · outbound

This paper cites Phase-functioned neural networks for character control,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Phase-functioned neural networks for character control,

Reference 5

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Source-reported events for the cited work

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

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Observation 6384ab7d-cbb1-4678-858a-d7dd9ea3f0cf · outbound

This paper cites Recurrent network models for human dynamics,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Recurrent network models for human dynamics,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.430894Z

Source-reported events for the cited work

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

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Observation 2a91dca3-d93f-4ab1-89fd-79f80913db12 · outbound

This paper cites In- teractive control of avatars animated with human motion data,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling In- teractive control of avatars animated with human motion data,

Reference 7

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raw_fallback, observed 2026-08-14T12:27:24.417038Z

Source-reported events for the cited work

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

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Observation 69427784-37cb-415c-99b5-8ba056e0eb95 · outbound

This paper cites Planning biped locomotion using motion capture data and probabilistic roadmaps,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Planning biped locomotion using motion capture data and probabilistic roadmaps,

Reference 8

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raw_fallback, observed 2026-08-14T12:27:24.403451Z

Source-reported events for the cited work

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

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Observation f62bc5db-b554-4472-9e3b-8d9bc4927f12 · outbound

This paper cites Natural character posing from a large motion database,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Natural character posing from a large motion database,

Reference 10

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raw_fallback, observed 2026-08-14T12:27:24.375527Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.547802Z digest=sha256:b4d9de1c929d7bca8ff784ab25ec61d59bbc384ce53bcf515df6c3d3c2d5fb0b

Observation dce3406e-5a7b-4e2e-8509-dbb27c502b3b · outbound

This paper cites Spectral style transfer for human motion between independent actions,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Spectral style transfer for human motion between independent actions,

Reference 11

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raw_fallback, observed 2026-08-14T12:27:24.362330Z

Source-reported events for the cited work

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

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Observation ca5f66ac-aee0-42ea-9adc-a3e6fe811cf4 · outbound

This paper cites Realtime style transfer for unlabeled heterogeneous human motion,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Realtime style transfer for unlabeled heterogeneous human motion,

Reference 12

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raw_fallback, observed 2026-08-14T12:27:24.349523Z

Source-reported events for the cited work

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

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Observation 1179df60-6917-4244-92b8-d6252623ce47 · outbound

This paper cites Spectral-based group formation control,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Spectral-based group formation control,

Reference 13

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raw_fallback, observed 2026-08-14T12:27:24.334271Z

Source-reported events for the cited work

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

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Observation ed8ecb8e-1583-4b9b-a947-bb78768e8456 · outbound

This paper cites Controllable data sampling in the space of humanposes,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Controllable data sampling in the space of humanposes,

Reference 14

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Source-reported events for the cited work

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

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Observation af648b3b-b007-4227-8c37-f95ea18ec93d · outbound

This paper cites Realtime human motion control with a small number of inertial sensors,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Realtime human motion control with a small number of inertial sensors,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.304915Z

Source-reported events for the cited work

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

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Observation 9e4eb29f-eafe-49df-94fe-42f16ab5f5d4 · outbound

This paper cites Synthesizing physically realistic human motion in low-dimensional, behavior- specific spaces,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Synthesizing physically realistic human motion in low-dimensional, behavior- specific spaces,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.291441Z

Source-reported events for the cited work

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

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Observation 9b982fb0-846f-4d5b-a44a-4c99e532964e · outbound

This paper cites Motion synthesis and editing in low- dimensional spaces: Research articles,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Motion synthesis and editing in low- dimensional spaces: Research articles,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.276393Z

Source-reported events for the cited work

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

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Observation 9cef7dcb-79d7-4237-8fd4-314ec7ff4572 · outbound

This paper cites Performance animation from low- dimensional control signals,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Performance animation from low- dimensional control signals,

Reference 18

Resolution
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raw_fallback, observed 2026-08-14T12:27:24.256379Z

Source-reported events for the cited work

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

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Observation bca803a6-953d-434e-8d56-50787042d224 · outbound

This paper cites Motion reconstruction using sparse accelerometer data,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Motion reconstruction using sparse accelerometer data,

Reference 19

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Source-reported events for the cited work

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

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Observation 2306cbea-a74f-43f1-8d93-0c5beb35b082 · outbound

This paper cites Real-time posture reconstruction for microsoft kinect,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Real-time posture reconstruction for microsoft kinect,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.224927Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.587416Z digest=sha256:a024efdb5ffa2ad34d2a3f7e964cefc429b402f7a540cb2b74777f933b9408fe

Observation 08c486f9-f838-4ab4-8997-f45dfd3f96c4 · outbound

This paper cites Kinect posture re- construction based on a local mixture of gaussian process models,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Kinect posture re- construction based on a local mixture of gaussian process models,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.212737Z

Source-reported events for the cited work

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

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Observation 67ca7ffd-a890-4b9f-87de-dfd61189e1d9 · outbound

This paper cites Example-based human motion denoising,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Example-based human motion denoising,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.199695Z

Source-reported events for the cited work

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

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Observation 37669c60-ed20-4c87-b7b4-f58a28524e05 · outbound

This paper cites Imagenet classi- fication with deep convolutional neural networks,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Imagenet classi- fication with deep convolutional neural networks,

Reference 23

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.603518Z digest=sha256:518243eb0360f4711d96f298c15fd0d2da1c3f284488e5ca3b04dba94655b7b6

Observation 416d30ea-31c2-49bc-aaed-dbc35d8b748a · outbound

This paper cites Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement 12 learning,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement 12 learning,

Reference 24

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raw_fallback, observed 2026-08-14T12:27:24.168374Z

Source-reported events for the cited work

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

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Observation b77e6319-e045-4ae4-82f3-23f068077ded · outbound

This paper cites On human motion prediction using recurrent neural networks.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling On human motion prediction using recurrent neural networks

Reference 25

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local_arxiv, observed 2026-08-14T12:27:23.874623Z

Source-reported events for the cited work

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

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Observation f5ad67b9-53c9-4c57-b56b-b8b4cfd78ae3 · outbound

This paper cites Auto- conditioned recurrent networks for extended complex human motion synthesis,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Auto- conditioned recurrent networks for extended complex human motion synthesis,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.152033Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.616259Z digest=sha256:1cad1dea42af279c7519fbb3b22af39b758cb0081a4ca5cad72b8fe19609e2e1

Observation 1ea68283-236d-4139-9d70-872e7a9f0f0d · outbound

This paper cites Hierarchical recurrent neural network for skeleton based action recognition,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Hierarchical recurrent neural network for skeleton based action recognition,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.137527Z

Source-reported events for the cited work

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

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Observation 3b9d44ff-7d0c-4abc-8a26-8d3c0a987acc · outbound

This paper cites Long-term recurrent convolutional networks for visual recognition and description,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Long-term recurrent convolutional networks for visual recognition and description,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.124661Z

Source-reported events for the cited work

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

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Observation 35da0947-0387-46fa-bf99-35e8033b79fe · outbound

This paper cites Recurrent attention models for depth-based person identification,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Recurrent attention models for depth-based person identification,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.110415Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.628790Z digest=sha256:bb6dabe05d4e2a37b92c01efd603b8f282a71e23c6999419c72fd0a32a8351d0

Observation acd16f9b-2b23-40f9-b76d-bcbe546739b3 · outbound

This paper cites Interactive character animation by learning multi-objective control,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Interactive character animation by learning multi-objective control,

Reference 30

Resolution
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raw_fallback, observed 2026-08-14T12:27:24.094865Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.633084Z digest=sha256:87a0fc043d2d50b3aea1b15d70f1bc14c93321e7684d69afc7f24647a5e15fb3

Observation e5da8829-8ea0-4264-9d04-c7ee9f1e166e · outbound

This paper cites Li and R.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Li and R

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.080329Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.636821Z digest=sha256:b5c8aa49b7504297fe99e16bd3dc775d2b4bb4b54b55d516b343c0039cf24712

Observation 66d90461-be18-4931-8ed8-6f373f9ca15b · outbound

This paper cites Learning spatio-temporal structure from rgb-d videos for human activity detection and anticipa- tion,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Learning spatio-temporal structure from rgb-d videos for human activity detection and anticipa- tion,

Reference 32

Resolution
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raw_fallback, observed 2026-08-14T12:27:24.066828Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.640877Z digest=sha256:db50d4ba291764acef055ccf1f5677efb062d3fc60bafe2e1d9154b0576b7838

Observation 09a5a356-219f-43a6-a2b7-bf96b7fa5b87 · outbound

This paper cites (2016) Cargnie mellon university motion database.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling (2016) Cargnie mellon university motion database

Reference 33

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raw_fallback, observed 2026-08-14T12:27:24.050264Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.644793Z digest=sha256:37a52c82c8b60daabdc68ab97e56d6d0c65a6b5f73269a5e6879719e9753bfcb

Observation 2d15ff49-bd8b-4faf-8e3f-6eb42daf34be · outbound

This paper cites Documentation mocap database hdm05,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Documentation mocap database hdm05,

Reference 34

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raw_fallback, observed 2026-08-14T12:27:24.032695Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.649440Z digest=sha256:6099b3cc16a9b0f6b4ced6f90cc18c3baa1ef5637d40fd3f604ff3e33894f76f

Observation 2d1aa0a2-ef5d-4eae-a381-20e41627f3d4 · outbound

This paper cites Berkeley mhad: A comprehensive multimodal human action database,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Berkeley mhad: A comprehensive multimodal human action database,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.016549Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.653432Z digest=sha256:a13ded810238d00b1badc8e7ea218b817a951e81d689e929221ce1ad6f768916

Observation 658e709b-e920-42fa-b326-7362288d33f1 · outbound

This paper cites Action recognition based on a bag of 3d points,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Action recognition based on a bag of 3d points,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.000487Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.657393Z digest=sha256:e7a159a271cfab0ccc79a0a9c59d01725421d89a1cb603803b166220cca7d49d

Observation 02d869dd-8457-4b4c-8e62-c8938c1785ba · outbound

This paper cites Modeling spatial and temporal variation in motion data,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Modeling spatial and temporal variation in motion data,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.986715Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.661382Z digest=sha256:52fd141d546f75b5882cb6f641225534d93b1f110623af63ca0e90db63e53246

Observation 19160cfe-5677-4de0-bdd7-7f29b8067b83 · outbound

This paper cites Gaussian process dy- namical models for human motion,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Gaussian process dy- namical models for human motion,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.970655Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.665104Z digest=sha256:d3a60a2fb7c7d7143b4b6b91596f3103e9f956a9b36fc3b90953a110f3bba240

Observation 9c6eefd6-596f-4404-b410-b93abb038df2 · outbound

This paper cites Long short-term memory,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Long short-term memory,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.669074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.669074Z digest=sha256:66ab71a67109fbb0dd2e9ac8246abc4aa04141a1bc5b2174cc40c585f5da0c0e

Observation 535169d2-b75a-4abf-97e7-ada423cd5849 · outbound

This paper cites Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.673391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.673391Z digest=sha256:c285f17cb204dcf71bd2ae48ea6be0ec51b98396a7e28850968b73c95c6bd82f

Observation 5004b652-a45f-4b96-8439-b2bf600f6a1e · outbound

This paper cites Sequence to Sequence Learning with Neural Networks.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Sequence to Sequence Learning with Neural Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.677747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.677747Z digest=sha256:70f845d0b87f1382ab4c09ba62f15933a515ee0f03d1eae24ccf68c84b7c4420

Observation f0697e33-08ad-4f22-86e8-344838f72870 · outbound

This paper cites Unsupervised Learning of Video Representations using LSTMs.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Unsupervised Learning of Video Representations using LSTMs

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.682638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.682638Z digest=sha256:c0fee7a5a847732ab9444af6c805f60ed98e307ecdd1d18424070b6efce1fba6

Observation ca7644a6-0e46-43e5-9b18-b865e24ae4cb · outbound

This paper cites Style- based inverse kinematics,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Style- based inverse kinematics,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:24.388833Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.686893Z digest=sha256:56450a0ad57de5defec0faa800a25b2652aed8e738e75a8dc8f48c3ea95c7191

Observation 9e39a3d9-ed9d-49de-9f11-5aa85b547dbe · outbound

This paper cites Dropout: A simple way to prevent neural networks from overfitting,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Dropout: A simple way to prevent neural networks from overfitting,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.946541Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.691108Z digest=sha256:80cdd454913efea8a135da1c703fda0f78ad1fd0b33b90233401ea535bff83e2

Observation c3b31d0e-2e8e-4aa5-b3cf-707d106a1c3c · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.695780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.695780Z digest=sha256:6a8132af23a7692a580014efee104893dceba3308726320246ac106751ffd24c

Observation 2ec6c316-7d42-4656-8149-142ec255a15e · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.700206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.700206Z digest=sha256:32c0b73b334517dfe3d026aea204227d060374c0527edd8cca12c70d159fd914

Observation 863a6632-16c6-4ba5-b5ec-6ec544cae5dc · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling ADADELTA: An Adaptive Learning Rate Method

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.704576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.704576Z digest=sha256:b2bac1dc41965e847b2baefeccabf0e6341c7853987dceeb122fdfee89481de5

Observation 1d7920a4-1289-4a04-84b9-a827ca7eaeb9 · outbound

This paper cites Real-time physical modelling of character movements with microsoft kinect,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Real-time physical modelling of character movements with microsoft kinect,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.932272Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.708719Z digest=sha256:6a8959f1240a1d1a12712d3f8c2b04fd903d7fec1ac6b78eef41da7a50d32e29

Observation fc36beb1-a5fa-4d99-94a6-579ae8024ba3 · outbound

This paper cites Hu- man3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Hu- man3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.919712Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.712596Z digest=sha256:4ae729430e0fcfc73aad395bf4acdb6809cba28db69b835c122af34ea08cf0aa

Observation 18ed57dd-99ab-4b65-9af2-22e18060d11d · outbound

This paper cites Learning motion manifolds with convolutional autoencoders,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Learning motion manifolds with convolutional autoencoders,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.906285Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.716629Z digest=sha256:2bf46876c3dab0781b4652d623af180d73c58b806c44d6fa6dfe96f72f5a029f

Observation 8ed5f731-8b86-49b3-b623-c16bc72286d1 · outbound

This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.720709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.720709Z digest=sha256:05768b3b5fc59668749801b5f1b2363b3371ca86c97065b5f902b8a891288ab9

Observation d45fe5b5-bdb9-4fae-b993-368955a3fdc8 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-14T12:27:23.725091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:27:23.725091Z digest=sha256:5a35b8a4294a35857524d7027cf03361c70b7c3a45c1386e4c58dea47d4a824c

Observation 87bbdf9d-01e2-496e-8c8f-f83a247f3d23 · outbound

This paper cites Latent structured models for human pose estimation,.

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling Latent structured models for human pose estimation,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T12:27:23.891808Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T12:27:23.729103Z digest=sha256:22677c10f45ab9c2dd3cea4ffa51ed05f96bc209be3588f3abb69f9aa16f42a9

Pith citing papers

Observation d4b6ac73-3c7f-4cf8-a90b-9cdffa82d675 · inbound

Motion Generation Review: Exploring Deep Learning for Lifelike Animation with Manifold cites this paper.

Motion Generation Review: Exploring Deep Learning for Lifelike Animation with Manifold Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-08-11T17:24:38.932404Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T17:24:38.406290Z digest=sha256:cd5e41f72482aa490d806e7eb35bd97e43cf28485e1c2a82b7d97731cb6427dc